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RESEARCH ARTICLE |
1 Institute on Aging, University of Wisconsin-Madison.
2 Office of Population Research, Princeton University, New Jersey.
Address correspondence to Carol D. Ryff, Institute on Aging, 2245 Medical Science Center, University of Wisconsin-Madison, 53706. E-mail: cryff{at}wisc.edu
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Abstract |
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 TOP Abstract Genes Associated With Disease:...Promoting a Focus on...Social Environments and Positive...Future Directions: Linking...References |
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THE age of genomic science and genomic medicine has, paradoxically, put a spotlight on the environment. Remarkable strides in molecular genetics have, for example, demonstrated that genes associated with susceptibility to certain diseases do not fully determine disease status. Discrepancies between risk status based on genotype and disease symptomatology are prominent across numerous health outcomes, thus calling for greater emphasis on the role of environments in preventing expression of genetic predispositions for disease. Because the social environment has been extensively studied as a prominent influence on health, we propose that research on the genetics of aging should incorporate an explicit focus on the social world. Moreover, a growing literature is advancing understanding of the mechanistic processes through which social relationships contribute to health outcomes. Surprisingly little of this research (whether epidemiologic or neurophysiologic) intersects, however, with studies of the genetics of aging. Thus, there is need to bring the social world more explicitly into genetic analyses and, simultaneously, promote greater emphasis on genetic factors among those who study social relationships and health.
The specific objectives of the article are threefold: (1) to bring to extant research on the genetics of aging (both behavioral and molecular) an explicit emphasis on the social environment as a prominent influence on pathways to health and illness; (2) with the social environment in mind, to advocate for a new era of scientific inquiry (again, both behavioral and molecular) focused explicitly on gene–environment interactions; and (3) to underscore the potential protective influence of positive social environments in preventing, or delaying, the onset of disease, even in the presence of genetic risk.
To accomplish these objectives, we will first selectively review extant knowledge on genes that have been associated with disease outcomes. A central feature of this review is the recurring evidence that many who carry genes (or, more precisely, one version of that gene, called an allele) for particular diseases do not necessarily show disease symptomatology. This empirical reality demands greater attention to clarify how some individuals, despite genetic risk, do not succumb to particular disease outcomes. We will then examine recent findings, in both human and animal models, which point to the pivotal importance of environments in understanding phenotypic outcomes, even in the face of known genetic risk. Underscoring the importance of gene–environment interactions, such research also highlights the potential of positive social environments to effect change, both in genetic expression and in behavioral phenotypes.
We then provide a selective look at studies (epidemiologic and mechanistic) that have linked the social environment to health. This work is included to clarify advances that have already occurred in measuring the social environment and identifying its critical features, such as emotional experience, for activating neurophysiology. It is in this section that we highlight some of our own recent empirical findings, including studies that have addressed the role of positive social relationships in promoting resilience (i.e., the capacity to maintain, or regain, health and well-being in the face of adversity). In recent literature on resilience, there has been growing interest in possible contributions of genetics as well as other neuroendocrinologic, immunologic, emotional, and cognitive factors to resilient functioning (Curtis & Cicchetti, 2003
; Charney, 2004).
We conclude with a set of new directions for future research. Recommended initiatives include incorporating assessments of social environments in studies of both behavioral and molecular genetics to investigate their possible role in explicating why some, even in the face of known genetic risk, do not progress to disease symptomatology. We also suggest ways in which behavioral and molecular genetics might be incorporated into ongoing epidemiologic and neurophysiologic studies that connect social relationships to health. Overall, our perspective does not reflect a disease-specific formulation but rather emphasizes the possible role of social factors across diverse health outcomes.
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GENES ASSOCIATED WITH DISEASE: RISK GENOTYPE STATUS  DISEASE STATUS
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TOPAbstractGenes Associated With Disease:...Promoting a Focus on...Social Environments and Positive...Future Directions: Linking...References |
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; Snowden, Greiner, & Markesbery, 2000). Here is where assessments of daily activities (e.g., diary studies) on populations screened for APOE variants (termed alleles, such as E2, E3, and E4) would be valuable for elucidating Gene x Environment interrelationships. Motivating such human studies is animal research, focused on rats and nonhuman primates, which indicates that neurogenesis is promoted by engagement in "enriched environments" (Gould, Reeves, Graziano, & Gross, 1999a; Gould, Tanapat, Hastings, & Shors, 1999b; Gross, 2000) and that physical exercise up-regulates brain-derived neurotrophic factor and nerve growth factor in the hippocampus (Neeper, Gomez-Pinella, Choi, & Cottman, 1996; Oliff, Berchtold, Jackson, & Cottman, 1998). The latter studies suggest that exercise may help increase or restore neurotrophin levels in the aging brain.
Second, with regard to breast cancer and colorectal cancer, there is considerable epidemiologic evidence implicating social environmental and behavioral factors in preventing and/or delaying the age at onset of these diseases (Kere, 2001; Perera, 1997). There is also substantial variation among different populations in frequencies of susceptibility alleles (e.g., susceptible alleles in BRCA1 and BRCA2 have a higher frequency among Finnish and Ashkenazi Jewish women than the general U.S. population of women). Variation in susceptibility allele frequency is attributable to the unusual social and demographic histories of populations such as the Finns and Ashkenazi Jews. In particular, during past population bottlenecks, mutations present at low frequencies could increase because of random gene frequency drift. In addition, consanguineous marriages also facilitated the maintenance of susceptibility gene frequencies in populations (Kere, 2001; Risch et al., 2003). Founder effects and genetic drift, but without a strong inbreeding component, are the key elements in the occurrence of 22 Mendelian diseases occurring at unusually high prevalence in subpopulations in Quebec, Canada (Scriver, 2001). Missing, however, are in-depth characterizations of the environments of people who carry susceptibility alleles for breast and colorectal cancers, type 1 and type 2 diabetes, rheumatoid arthritis, and a host of other diseases but do not ultimately manifest these diseases. Such studies could provide the basis for prevention programs applicable to persons screened for particular susceptibility genes.
An important feature of the type 1 diabetes example is the point that even for those people who have both susceptibility genes (i.e., the human leukocyte antigen [HLA] genotype DQ3.2 and DQ2) and a family history of insulin-dependent diabetes mellitus, the probability of eventual onset of disease is only.25. Thus, 75% of the people with this genetic risk profile do not progress to disease status. A second point concerns the increase in risk associated with having a family history of insulin-dependent diabetes mellitus beyond that associated with just having the two HLA susceptibility genes. This implies that there are other non-HLA genes in the family or as yet undiscovered HLA susceptibility genes for type 1 diabetes beyond what we have indicated here (Nepom, 1995).
The central message of Table 1 is that even when susceptibility genes are linked with high disease probabilities at late ages, there are likely to be environmental influences that are protective for those who do not progress to disease status at all. More generally, there is great variation in age at onset of disease for those who have susceptibility genes and do progress to disease status. The role of environmental influences in understanding such variability has received little attention.
Going beyond Table 1, there is a growing list of candidate susceptibility genes for coronary heart disease (CHD) (Breslow, 2001). The molecular analyses are an important complement to twin studies of risk for CHD (Marenberg, Risch, Berkman, Floderus, & de Faire, 1994). There are also mutations such as LDLR that predispose people to familial hypercholesterolemia, a precursor of heart disease (Kere, 2001). In the 1960s and 1970s, North Karelia in Finland was a region with especially high rates of CHD, heart disease mortality, and high gene frequencies for familial hypercholesterolemia. However, over a span of 25 years, an intensive community-based intervention program, focused on reducing smoking, modifying diets, and promoting strong community cohesion on behalf of public health, drastically reduced heart disease rates and CHD mortality (Puska, Tuomilehto, Nissinen, & Vartianen, 1995). From 1969–71 to 1995, the age-standardized CHD mortality (per 100,000) decreased in North Karelia by 73% (from 672 to 185). Over the same time period, lung cancer mortality in men decreased by 71% and overall CVD mortality by 61%. In women, CHD mortality decreased by 68% and overall CVD mortality by 64% (Puska, Vartianen, Tuomilehto, Salomaa, & Nissinen, 1998).
The multifaceted features of this program included (a) workplace programs oriented toward weight loss, smoking cessation, and the availability of vegetables at canteens; (b) cholesterol-lowering competitions between villages in North Karelia; (c) a lay leaders program promoting discussion about smoking and diet when people met on the street; (d) antismoking legislation, the elimination of all advertising about it, and prohibition of indoor smoking in most public places; and (e) a coordinated initiative with food manufacturers and supermarkets focused on low-fat diets and the reduction of salt in multiple food products. Many people with genetic predispositions to CHD did not actually manifest the disease as a result of these environmental/behavioral modifications.
A useful follow-up investigation would be to characterize the life histories of those in the North Karelia study with different combinations of genetic susceptibilities. There may well be considerable variation in behaviors and social environments in this population that could provide a deeper understanding of how changing environments can override genetic susceptibility to heart disease. An interesting start in this direction is the study of Vuorio and colleagues (Vuorio, Gylling, Turtola, Kontula, Ketonen, & Miettinen, 2000), where stanol ester margarine proved to be a safe and effective hypolipidermic treatment in heterozygous familial hypercholesterolemia families in North Karelia comprising both adult individuals and children aged 3–13. The motivation for this dietary intervention was a prior literature showing that stanol esters lower the serum cholesterol level by inhibiting cholesterol absorption (Miettinen, Puska, Gylling, Vanhanen, & Vartiainen, 1995).
Across the types of diseases discussed above, the central point we underscore is the variability and flux in disease probability rates among those with known susceptibility gene status. Even where such rates are high in later life (e.g., probability of having Alzheimer's disease if one has two copies of the APOE4 gene, probability of having breast cancer if one has BRCA1 or BRCA2 susceptibility alleles), there is considerable variation in age at onset. The extent to which onset can be delayed by environmental intervention is a critical, but insufficiently studied, issue, despite growing evidence that positive environments do, indeed, affect neurobiological processes. That is to say, a new era of research needs to be initiated that blends the tools and talents of genetic researchers with those having expertise in assessing environmental influences to understand the pathways to diverse health outcomes (mental and physical). Why? Because the two working together may well be able to identify factors that could significantly reduce disease probability rates, even in the face of known genetic susceptibility. For a useful start in the context of depression, see Charney & Manji (2004).
This point has not been lost by those who advocate for population screening in the age of genomic medicine (Khoury, McCabe, & McCabe, 2003). Key principles of population screening include the following: (a) identification of persons likely to be at high risk for a specific disorder so that further testing can be done and preventive actions taken, (b) outreach to populations that have not sought medical attention for the condition, and (c) follow-up and interventions to benefit the screened persons (Wald, 2001). Taking preventive actions and providing appropriate interventions require a scientific knowledge base about factors that reduce the likelihood of progressing toward disease manifestation.
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PROMOTING A FOCUS ON GENE–ENVIRONMENT INTERACTIONS |
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TOPAbstractGenes Associated With Disease:...Promoting a Focus on...Social Environments and Positive...Future Directions: Linking...References |
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Rutter and Silberg (2002), for example, in a recent review of research on gene–environment interplay for understanding emotional and behavior disturbance, make the following observation:
Nevertheless, all too often, behavior genetic findings have been presented in terms of a partitioning of population variance into separate additive and nonadditive genetic components and shared and nonshared environmental effects, with a disregard for the possible role of rGE (gene–environment correlations) and G x E (gene–environment interactions). That is now changing because of a greater realization of the crucial role of gene–environment interplay in risk and protective processes and because of advances in the means to study such interplay. (p. 464)
Similar points have been made at the molecular level: "Whether a gene is expressed and the degree to which it is expressed depend strongly on the environmental conditions experienced by the organism" (Singer & Ryff, 2001, p. 63; also, Curtis & Cicchetti, 2003). The critical questions are thus those of environmentally induced gene expression. Thus, neither genes nor the environment dominates, but rather there is continual interaction between the two, with phenotypes emerging as a function of this constant dialogue. The Human Genome Project and microarray chip technologies offer researchers remarkable new tools for detecting gene expression with unprecedented resolution (Botstein & Risch, 2003). However, "realizing the full potential of whole genome analyses will require multidisciplinary research projects that integrate molecular biology with physiology and the behavioral and social sciences" (Singer & Ryff, 2001, p. 64; also Curtis & Cicchetti, 2003).
An important instance of this interplay is exhibited in studies of honeybee colonies (Robinson, 2002). For example, there is a strong negative association between the proportion of old bees in a colony and the proportion of precocious foragers. Old bees inhibit the maturation of younger bees. In addition, pheromones from the queen and brood fine-tune the pace of worker behavioral maturation, with a primary role ascribed to worker–worker interactions that are also possibly chemically mediated. This suggests that pheromones may affect the expression of genes involved in honeybee behavioral maturation.
Multiple studies have shown that bees of some genotypes show a faster rate of maturation and make the transition from working in the hive to foraging at a younger age than workers of other genotypes (Guzman-Novoa, Page, & Gary, 1994). There is also genotypic variation for endocrine and social factors that can influence behavioral maturation. Examples are juvenile hormone and sensitivity to social inhibition (Giray, Guzman-Novoa, Huang, & Robinson, 2000b). However, there seems to be no obligate link between variation in the age at onset of foraging and variation in specific physiologic and social factors. For example, even though the age at onset of foraging can be experimentally manipulated by hormone treatment or exposure to social inhibition, genotypes with faster rates of maturation do not always have higher juvenile hormone titers or lower sensitivity to social inhibition than genotypes with slower rates of behavioral development. One implication of this fact is that variation in the rate of behavioral maturation can be influenced by the actions of different networks of genes in bees with different genotypes.
Adding to the subtlety of these relationships, recent behavioral evidence suggests that genes that influence the rate of worker behavioral maturation can also affect other traits. Several intrinsic and extrinsic factors are already known to contribute to a colony's level of defensiveness (Giray, Guzman-Novoa, Aron, Zelinsky, Fahrbach, & Robinson, 2000a). Bees from genotypes that start foraging at a younger age tend to have colonies that are more defensive. These results suggest that in a complex animal society, the effects of genes on behavior will often involve circuitous pathways that require comprehensive behavioral analysis at both the individual and the group levels.
Moving back to humans, what is the evidence to date of such joint effects of genotype and environment? Rutter and Silberg (2002) summarize studies from both molecular and quantitative genetics. With regard to the former, they show that risk for Alzheimer's disease is associated not only with the APOE4 allele (Plassman & Breitner, 1996; Rubinzstein, 1995) but further clarify that head injury notably sharpens the associated risk. Mayeux and colleagues (1995) found no increase in risk for Alzheimer's disease associated with head injury in the absence of APOE4, a 2-fold increase with APOE4 alone, but a 10-fold increase from the combination of APOE4 and head injury. Similarly, Teasdale, Nicoll, Murray, and Fiddes (1997), in a 6-month follow-up of patients with a severe head injury, found that APOE4 individuals were more than twice as likely to have a bad outcome. APOE4 has also been linked to other diseases, such as ischemic heart disease, which undoubtedly involves complex multifactorial causation. Humphries and colleagues (2001) found that APOE4 was a risk factor, but this applied mainly to smokers. Talmud, Bujac, Hall, Miller, and Humphries (2000) found that individuals with the D9N allele for lipoprotein lipase had a markedly increased risk for ischemic heart disease when they smoked, with the risk associated with smoking being much less in those who did not have this allele. Environmental influences are thus prominent in understanding these pathways to disease status.
Quantitative genetics also provides growing evidence of joint effects of genotype and environment, particularly in understanding pathways to psychopathology (Rutter & Silberg, 2002). Studies of adoptees, for example, have shown that the effects of adverse social environments (adoptive parents with antisocial disorders, anxiety/depression problems, alcohol/drug problems, or marital problems) contribute to increased risk of aggressivity and conduct disturbance among those with genetic risk (crudely indexed by antisocial behavior in biological parent) but not among those without genetic risk (Cadoret, Cain, & Crowe, 1983; Cadoret, Yates, Troughton, Woodworth, & Stewart, 1995). Research on adult offspring of alcoholic biological parents has shown that major depression in females was associated with an alcoholic genetic diathesis, but only when combined with disturbance in an adoptive parent (Cadoret et al., 1996). Similarly, twin research has shown that risk for substance abuse in adolescence involves a significant interaction such that the familial risk (parent with substance abuse/dependence) effect was greater in the presence of high environmental risk (deviant peers) (Legrand, McGue, & Iacono, 1999). Finally, Kendler and colleagues (1995) assessed risk for major depression as a function of genetic factors (monozygotic co-twin affected or unaffected by depression, dizygotic co-twin affected or unaffected by depression) and environmental factors (presence of major life event). They found that risk of onset of major depression following such an event was greatest in those at greatest genetic risk. This effect implied that genetic factors operated in part by affecting the sensitivity of individuals to the depression-inducing effects of stressful live events.
The above studies sketch key findings from prior studies of the joint effects of genotype and environment. These are usefully augmented with a more detailed look at specific studies of the joint effects of genotype and environment, both human and animal. Below we describe research that speaks directly to the importance of social environments. The first studies with humans underscore the point that adverse social environments do not, in themselves, strongly predict behavioral disorders but rather that such outcomes are notably more likely among those with genetic vulnerability. The subsequent studies with animals carry the significance of social environments to notably higher levels by asking whether pre-existing genetic vulnerability and behavioral phenotypes can be changed in more positive directions by modification of the social environment. This is the essence of environmentally induced gene expression, in the service of promoting positive health (Singer & Ryff, 2001).
Caspi and colleagues (2002) addressed the question of why some children who are maltreated grow up to develop antisocial behavior, whereas others do not. Boys who experience erratic and punitive parenting are at risk of developing conduct disorders and antisocial personality symptoms and becoming violent offenders, but there are large differences between children in their response to maltreatment. Most, in fact, do not become delinquents or adult criminals. Their study focused on individual differences at a functional polymorphism in the promoter of the monoamine oxidase A (MAOA) gene to characterize susceptibility to later-life antisocial behavior among persons exposed to maltreatment in childhood. This gene encodes the MAOA enzyme, which metabolizes neurotransmitters such as norepinephrine, serotonin, and dopamine, rendering them inactive (Shih, Chen, & Ridd, 1999). Genetic deficiencies in MAOA activity have been linked with aggression in mice and humans (Rowe, 2001). Thus, their hypothesis was that childhood maltreatment predicts adult antisocial behavior primarily among those male children whose MAOA is insufficient to constrain maltreatment-induced changes to neurotransmitter systems.
The question was investigated with members of the Dunedin Multidisciplinary Health and Development Study, a representative general population sample. Sample members had well-characterized environmental adversity histories between the ages of 3 and 11 and provided multiple indicators of adult antisocial behavior, a complex phenotype. Findings revealed a significant interaction between MAOA activity and maltreatment, such that the effect of childhood maltreatment on antisocial behavior was significantly weaker among males with high MAOA activity. This pattern of findings was consistent for all four antisocial outcomes (conduct disorder, conviction for violent crimes, personality disposition toward violence, and symptoms of antisocial personality). For example, the odds of conduct disorder were 2.8 times greater among maltreated males with low MAOA activity than nonmaltreated males with this genotype. In contrast among males with high MAOA activity, maltreatment did not confer significant risk for conduct disorder. Similarly, maltreated males with low MAOA activity were 9.8 times more likely to be convicted of violent crime than nonmaltreated males with this genotype. And, again, among males with high MAOA activity, maltreatment did not confer significant risk for violent conviction.
This study is important for underscoring two points. The first, consistent with our repeated emphasis, is that genetic risk alone does not always determine adverse outcomes. Those with low MAOA activity were not inevitably destined for lives of adult misconduct, disorder, and crime. It was only when this genetic profile was combined with childhood maltreatment that risk for adult problems was notably enhanced. The second point, not emphasized in the article but illustrated by the data, is that even among those males who had both genetic and environmental risk, negative adult outcomes were not inevitable. Approximately 20% of those males with low MAOA activity and severe maltreatment did not show conduct disorder. When low MAOA activity was combined with probable maltreatment, the percentage moved to 60% who showed no conduct disorder. Moreover, for adult violent convictions, > 70% of those with both MAOA activity and severe maltreatment had not been convicted of a violent crime. How such individuals managed to evade the negative outcomes associated with their endowed risk as well as their adverse family history cannot be answered by the data provided and may well involve combinations of other genetic and environmental influences.
A second study by Caspi and colleagues (2003) addressed a different combination of genetic and environmental influences that predispose some individuals to experience major depression. These analyses, based on the same Dunedin longitudinal sample, involved assessment of life stressors (the environmental input) and a functional polymorphism in the promoter region of the serotonin transporter (5-HTT) gene. The short (s) allele in the gene-linked polymorphic region has been associated with lower transcriptional efficiency of the promoter compared with the long (l) allele. At age 26, 847 sample members were divided into three groups based on whether they had two copies of the short allele, one copy of the short allele, or two copies of the long allele. Stressful life events (employment, financial, housing, health, relationship stressors) occurring after their 21st birthday and before their 26th birthday were also assessed.
Using a moderated regression framework with sex as a covariate, they found a significant interaction between the 5-HTT genotype and life events in predicting depressive symptoms at age 26. The effect of life events on depression was shown to be significantly stronger among individuals carrying an s allele than among the l/l homozygotes. They further demonstrated that individuals carrying an s allele whose life events occurred after their 21st birthday experienced an increase in depressive symptoms from age 21 to 26. The Gene x Environment interaction showed that stressful events predicted a diagnosis of major depression among carriers of an s allele (but not among 1/1 homozygotes) even among those who did not have a prior history of depression. Childhood maltreatment also predicted adult depression only among individuals carrying the s allele, but not among 1/1 homozygotes.
This study is a compelling illustration of the gains in predictive precision that follow from investigating Gene x Environment interactions. As the authors note, much prior genetic research has been "guided by the assumption that genes cause diseases" (p. 389), but direct paths from genes to disease have not proven fruitful for complex psychiatric disorders. Their focus on environmental pathogens, in combination with genetic vulnerabilities, affords a notable advance. That said, this study, like its predecessor, makes a second dramatic point: namely, that among those with both genetic (s genotype) and environmental (more than four stressful events) risk, most (67%) did not become depressed. Similarly, among those with the s genotype and three stressful events, > 70% did not become depressed. These observations highlight the need for greater understanding of protective factors that contribute to healthy outcomes, despite notable profiles of both genetic and environmental risk (Ryff & Singer, 2002).
Deeper understanding of the mechanisms of gene expression vis-à-vis particular environmental influences has been, and will continue to be, pursued with animal models (see Singer & Ryff, 2001, for summary). For example, the behavior of rat mothers toward their offspring, namely licking and grooming (LG) and arched-back nursing (ABN), has been shown to program the expression of genes regulating neuroendocrine response to stress in adulthood among those offspring (Francis, Champagne, Liu, & Meaney, 1999a; Lui et al., 1997). As adults, the offspring of low-LG/ABN mothers exhibit increased fearfulness relative to offspring of high-LG/ABN mothers (Caldji, Tannenbaum, Sharma, Francis, Plotsky, & Meaney, 1998). They also show increased corticotropin-releasing factor (CRF) receptor levels in the locus ceruleus and decreased central benzodiazepine receptor levels in the basolateral and central nucleus of the amygdala, as well as increased CRF mRNA expression in the central amygdala. Predictably, stress-induced increases in levels of norepinephrine in the paraventricular nucleus of the hypothalamus were significantly higher in the offspring of low-LG/ABN mothers (Francis, Diorio, Liu, & Meaney, 1999b). These are all neurophysiologic signs of elevated reactivity to stress in adulthood.
Other recent studies, in both rats and nonhuman primates, have examined whether individual differences in maternal behavior are transmitted across generations. In rats, the female offspring of high-LG/ABN mothers show significantly more LG and ABN than female offspring of low-LG/ABN mothers (Francis et al., 1999a,b). In rhesus monkeys, there is clear evidence for intergenerational transfer of rejection of infants by mothers (Suomi, 1987; Suomi & Levine, 1998). In vervet monkeys, daughters reared by mothers who consistently spent a large amount of time in physical contact with their offspring became mothers who were similarly more attentive to their offspring (Fairbanks, 1989).
Cross-fostering paradigms in animal models underscore the important element of plasticity: the extent to which genetically determined trajectories can be modified in response to new environmental signals. In terms of behavioral measures of fearfulness or the hypothalamic–pituitary–adrenal axis response to stressful experiences, biological offspring of low-LG/ABN mothers cross-fostered onto high-LG/ABN mothers are indistinguishable from the natural progeny of high-LG/ABN mothers (Francis et al., 1999a,b; Weaver et al., 2004). In addition, these behavioral effects are reflected in corresponding changes in CRF gene expression in the hypothalamus and amygdala. Moreover, in adult females of both the cross-fostered and the natural progeny groups, their maternal behavior was typical of high-LG/ABN mothers.
These examples emphasize the potential for traits to be modified by environmental interventions and also clarify the gene expression that accompanies such interventions. Most important, they cast the social environment in a new light: Whereas previously conceived as an external influence that can increase or decrease risk of particular outcomes (behavioral phenotypes, disease status) in the face of known genetic risk, the cross-fostering studies demonstrate the potential of beneficial social environments to alter genetic expression and behavioral phenotypes. Such work adds to the importance of studying social environments as critical elements in understanding pathways to positive health.
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SOCIAL ENVIRONMENTS AND POSITIVE HEALTH: WHAT ARE THE MECHANISMS? |
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TOPAbstractGenes Associated With Disease:...Promoting a Focus on...Social Environments and Positive...Future Directions: Linking...References |
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; Cacioppo et al., 2002; Cohen, Underwood, & Gottlieb, 2000; Kiecolt-Glaser & Newton, 2001; Ryff & Singer, 2001; Uchino, Cacioppo, & Kiecolt-Glaser, 1996). Current inquiries encompass laboratory as well as epidemiologic studies conducted by researchers from diverse biomedical and social behavioral fields in disease-specific as well as generic health contexts. We highlight particular strands of this broad-based research that have relevance for advancing knowledge of the genetics of aging, with emphasis on the themes articulated above, namely, how social environments contribute to positive health outcomes, even in the face of known genetic risk.
We have previously reviewed the literature on social relationships, with the aim of understanding their role in the maintenance of good health (Ryff & Singer, 2000). The empirical coordinates of the social world span extensive, largely separate literatures on attachment (Cassidy & Shaver, 1999; Hazan & Shaver, 1994); close, personal relationships—now designated as the field of "relationship science" (Reis & Patrick, 1996); and marital quality and family ties (Karney & Bradbury, 1995; Kiecolt-Glaser & Newton, 2001; Repetti, Taylor, & Seeman, 2002). Much of this work has not been explicitly concerned with health or, when linked to biology, has focused primarily on relational conflict and marital or family dysfunction. Alternatively, many who have connected the social world to health have done so in epidemiologic contexts (Berkman, 1995; Berkman & Kawachi, 2000; House, Landis, & Umberson, 1988; Seeman, 1996), which have emphasized largely the quantity rather than the quality of social ties. Still others have employed experimental manipulations to see if relational strengths buffer against adverse health outcomes, including the common cold (Cohen, Doyle, Skoner, Rabin, & Gwaltney, 1997).
Taken as a whole, these differing lines of inquiry provide important pieces of the larger puzzle as to how the social environment impacts health, but they also make clear the need for new integrative research directions. For example, those who study the positive side of relational experience—be it attachment, intimacy, love, or what we have called "interpersonal flourishing"—need to have greater presence in health studies, particularly those focused on mapping the pathways (cardiovascular, neuroendocrine, immunologic) through which significant others impact biology. One potentially critical ingredient to the upside of social relations is emotion, which other researchers have shown is instantiated in neural circuitry (Davidson, Jackson, & Kalin, 2000) as well as neuroendocrine and immune function (Kiecolt-Glaser et al., 1997; Seeman & McEwen, 1996). Thus, we have emphasized that emotional experience in social relationships is likely a key element in mapping pathways to positive health outcomes (Ryff & Singer, 2001, 2003) and noted along the way, via input from others (Reis, 2001), that health-promoting relationships are likely those that involve blends of positive and negative emotions rather than a simple abundance of good, and an absence of bad, feelings.
To anchor these points empirically (e.g., how does one measure interpersonal flourishing and link it to mechanistic pathways?), we briefly describe some of our own recent findings. Beginning at the epidemiologic level, we used data from the Midlife Development in the United States (MIDUS) survey of adults aged 25–74 to show that those (both men and women) who report more positive relational experiences (i.e., affirmative answers to such questions as "How much does your spouse/partner really care about you? How much does he or she really understand the way you feel about things? How much can you open up if you need to talk about your worries?") and fewer negative relational experiences (i.e., negative answers to such questions as "How often does he or she argue with you? How often does he or she get on your nerves?") also reported better overall health, fewer chronic conditions, and fewer health symptoms (Ryff, Singer, Wing, & Love, 2001).
Linking cumulative relationship histories with biology necessitates the introduction of concepts and measures that reflect the body's responses to challenge and the wear and tear induced by persistent and/or repeated challenges. In this regard, Sterling and Eyer (1988) introduced the notion of allostasis to represent physiologic coping mechanisms and adaptive responses that maintain homeostasis. Unlike homeostasis, where parameters such as pH, essential metabolism, and body temperature are maintained at constant levels, allostasis consists of adaptive processes that ensure this stability (Schulkin, 2004). For example, catecholamine and glucocorticoid elevations during physical activity mobilize and replenish energy stores needed for brain and body function under challenge. These adaptations, in turn, maintain essential metabolism and body temperature. In addition, the body pays a price for being forced to adapt to adverse psychosocial or physical conditions. We refer to this price as allostatic load. It increases when there is too much allostasis (i.e., adaptive responding to challenge) or the inefficient operation of response systems that are repeatedly turned on and off (McEwen, 2000, 2002).
We linked cumulative relationship histories, in which we distinguished those who had been on largely positive relational pathways from childhood to adulthood, from those on largely negative pathways, with an operationalization of allostatic load, a summary index of wear and tear on multiple physiologic systems (Seeman, Singer, Rowe, Horwitz, & McEwen, 1997). Allostatic load has been measured with diverse indicators of risk from the cardiovascular, neuroendocrine, metabolic, and sympathetic nervous systems. Longitudinal aging research had previously shown high allostatic load to be a significant predictor, over a 7-year period, of incident cardiovascular disease, decline in cognitive and physical function, and death (Karlamangla, Singer, McEwen, Rowe, & Seeman, 2002; Seeman, Rowe, McEwen, & Singer, 2001). More refined operationalizations of allostatic load and a discussion of the role of immune system measures in them are described by Singer, Ryff, and Seeman (2004).
Our question, however, was whether good relational experience (from childhood through adulthood) might constitute an important protective influence, in the sense of keeping allostatic load low. Using a subsample of the Wisconsin Longitudinal Study, involving adults in their mid-50s and on whom biomarkers were also assessed, we found that those who were on the positive relationship pathway (measured by assessing the quality of their ties to both mother and father in childhood as well as their levels of multiple aspects of intimacy—emotional, sexual, intellectual, recreational—with a partner in adulthood) were significantly less likely to have high allostatic load than those on the negative relationship pathway. The differences were more dramatic for men than women, but they were significant for both sexes (Ryff et al., 2001).
Data from the above midlife sample were combined with an older sample to extend the story (Seeman, Singer, Ryff, Love, & Levy-Storms, 2002). Although we lacked exact equivalence in measurement of social experience, we were able to show that the above findings were extended to adults aged 70–79. Specifically, men who were more socially integrated and those reporting more frequent emotional support from others had lower allostatic load scores than those lacking these relational benefits. However, no significant associations were seen for older women.
To sharpen scientific understanding of the protective power of good-quality social relationships, we have conducted several studies of resilience (see Ryff & Singer, 2002; Ryff, Singer, & Seltzer, 2002): that is, the capacity to maintain, or regain, health and well-being in the face of significant adversity. To what extent are social relationships critical elements in promoting resilience? The literature on resilience in childhood (Luthar, Cicchetti, & Becker, 2000; Werner & Smith, 2001) makes clear that having even one significant positive connection with someone (in or outside of the family) is a prominent feature of those who prevail in the face of major life challenges (e.g., parental alcoholism, parental schizophrenia, severe poverty). We have examined similar questions, with both qualitative and quantitative data and involving both self-reported health as well as biomarkers. Analysis of the biography of Mark Mathabane, a survivor of the horrors of poverty and apartheid in South Africa, for example, provided a powerful account of the sustaining power of a committed and tenacious mother and a nurturing grandmother in protecting him from a violent street life destined for early mortality (Singer & Ryff, 1997). Similarly, qualitative interviews from MIDUS (Markus, Ryff, Curhan, & Palmersheim, 2004) show that the social relational realm is the central theme in how those at the low end of the educational hierarchy describe their well-being and what makes their lives good.
Also using the MIDUS data, we have conducted quantitative analyses to show that there is greater variability in health and well-being as one moves down the educational hierarchy. This greater spread makes an important point: namely, that some who lack socioeconomic advantage are doing surprisingly well, that is, they have comparable health profiles to those who have advantaged socioeconomic standing. How is this possible? How have they defied the adverse health outcomes that characterize many others who lack educational attainment? We hypothesized that those who are socioeconomically resilient (i.e., they do not fit the downward socioeconomic status gradient in health) are individuals with good social relationship histories. Our findings supported these predictions, although the obtained patterns were more strongly evident for men than women (Ryff et al., 2004). Related analyses, not summarized here, also examined the potential protective influences of long-term religion and spirituality.
Finally, returning to links between social relationships and biomarkers, we used the Wisconsin Longitudinal Study biological subsample to show that those with persistent economic disadvantage were, as predicted, more likely to have high allostatic load than those having persistent economic advantage or showing upward mobility (Singer & Ryff, 1999). However, the more important finding was that among those with economic disadvantage, those who had had persistently positive social relationships showed reduced likelihood of having high allostatic load. The data were limited by a small sample and must therefore be considered preliminary, but they point toward the potential significance of good-quality relationships for keeping various biological systems in zones of healthy functioning. Further supportive evidence along these same lines has emerged from a longitudinal study of aging women (Ryff, Singer, & Love, 2004).
In sum, the literature we have briefly sketched on the topic of social relationships and health underscores the broad scope of this arena of science as well as the growing evidence that salubrious social connections have beneficial consequences for health, including specification of intervening pathways. Although our overview has given primary emphasis to biological pathways (e.g., via allostatic load), it is important to note that another important pathway is behavioral: that is, how our significant others help us practice good health behaviors. For example, the literature on smoking reveals that both men and women are less likely to be current smokers if they are married than if they are single, divorced, or separated (Chassin, Presson, Rose, & Sherman, 1996) and further documents that success at smoking cessation is facilitated by partner/social support (Coppotelli & Orleans, 1985; Kivz, Crittende, Madura, & Warnecke, 1994; Mermelstein, Cohen, Lichenstein, Baer, & Kamarck, 1986; Rose, Chassin, Presson, & Sherman, 1996). Thus, there are numerous possible routes through which the social world is implicated in health outcomes. Across this vast terrain of science, however, there is surprisingly little intersection with research on genetics. Therefore, in the next section, we examine possible directions for building bridges between those who study genetic factors in health and those who investigate social relational influences on health.
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FUTURE DIRECTIONS: LINKING STUDIES OF GENETICS AND THE SOCIAL ENVIRONMENT |
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TOPAbstractGenes Associated With Disease:...Promoting a Focus on...Social Environments and Positive...Future Directions: Linking...References |
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, 1998), which continues to be studied prospectively (MONICA Project, 2003), offers valuable opportunities to probe environmental and behavioral differences between those who do and do not manifest disease, with and without a given complement of susceptibility genes.
Studies of joint effects of genotype and environments extend and sharpen the future directions suggested above. At the level of quantitative behavioral genetics, such joint effects are already being studied, as our literature review revealed. However, when present in such inquiries, the social environment has disproportionately been studied as a realm of negative influence and vulnerability. Thus, emphasis has been given to the ways in which parents maltreat their children and subject them to their own behavioral (alcoholism) and emotional (violence, depression) problems (e.g., Cadoret et al., 1996; Caspi et al., 2002; Kendler et al., 1995). These environmental factors, in combination with genetic predispositions, have been shown to increase risk for maladjustment. Comparatively little emphasis has been given to the ways in which good-quality parenting, involving loving and nurturing relationships, might offset the vulnerabilities ensuing from one's genetic endowment. As noted by Caspi and colleagues (2002), many with genetic risk (low MAOA activity) did not grow into violent, conduct-disordered adults. It was only when they were subjected to child maltreatment that risk of such outcomes was notably enhanced. However, even among those with both genetic and environmental risk factors, adverse outcomes did not emerge for many. Similarly, the majority of those having genetic risk for depression (short allele of the 5-HTT gene) and who had been exposed to high life stress in early adulthood did not succumb to major depression. Among the factors that may have offset their combined genetic and environmental risk may be positive, nurturing, supportive relationships with parents, grandparents, teachers, or friends. Illustrating such influences, a recent study by Kim-Cohen, Moffit, Caspi, and Taylor (2004) utilized a twin design and quantitative genetics to document that maternal warmth, stimulating activities, and children's outgoing temperament were factors accounting for positive adjustment among children exposed to socioeconomic deprivation.
In animal studies of the joint effects of genotype and environment, the influence of high-quality social environments has been most dramatically demonstrated. These investigations demonstrate how the behavior of rat mothers programs the expression of genes regulating neuroendocrine response to stress and, further, how such patterns are transmitted across the generations (Caldji et al., 1998; Francis et al., 1999a,b; Lui et al., 1997). Most significant, however, is the finding that even among those who are genetically predisposed to maladaptive stress responses, the provision of a positive social environment (through cross-fostering) changes not only the behavior and biology but also the underlying genetic expression. This is compelling evidence for the importance of studying social environments as fundamental influences on not just behavior, neurophysiologic substrates, and long-term health outcomes, but unfolding gene expression.
Finally, the vast research currently in progress under the broad rubric of social relationships and health is open territory for incorporating genetic agendas, which have been remarkably absent thus far. How might the genetics of aging, broadly defined, be brought into these studies? One avenue is by embedding twins in epidemiologic and longitudinal studies. This would be an important complement to extant longitudinal studies of twins, which have primarily been of interest to those trained in genetics (behavioral or molecular). An additional approach is to incorporate twins in population-based investigations. So doing would facilitate greater interplay between social behavioral, biomedical, and genetics researchers.
The MIDUS national survey, in fact, adopted this research design. In addition to > 3,000 respondents from the main probability sample, the study was augmented by a sample of > 900 pairs of twins as well as nearly 900 siblings. Establishing the first national sample of twins ever assembled, MIDUS brought genetic questions directly into the agendas of other social and behavioral researchers. For example, in-depth study of daily stressors, conducted with subsamples from the main sample and the twin sample, has shown that although genetic factors account for part of the variance in daily stressors, the larger influences follow from nonshared environmental factors (Neiss & Almeida, 1999). Other analyses have documented both genetic and environmental influences on personality traits (Johnson & Krueger, 2004). The new round of data collection (funded by the National Institute on Aging) includes comprehensive biomarker assessments on a large subsample of MIDUS respondents, including twins (only monozygotic pairs). Thus, in testing the extent to which psychosocial (e.g., personality characteristics, social relationships) and environmental (e.g., chronic and acute stressor) factors influence health outcomes and intervening biomarkers, the MIDUS design will also allow for investigation of genetic factors.
A major opportunity for understanding environmental influences arises in investigations of discordant twin pairs. Because of its large twin sample, MIDUS II provides an opportunity to examine the impact of discordant social relationship histories among monozygotic pairs on a diverse array of biomarkers and health outcomes. More generally, in the combined mono- and dizygotic twins and nontwin sibling pairs, it will be possible to investigate health profiles as a function of concordant and discordant social relationship histories. In areas where disease susceptibility genes have been ascertained, other future analyses may target specific genes and alleles (e.g., APOE4) as they interact with particular environmental influences (e.g., relationship histories), thereby providing unique opportunities for investigating gene–environment interactions. Beyond these substantive areas of inquiry, a further rationale for embedding twins in population-based studies is to provide much needed information on how twins compare with nontwins in sociodemographic, psychosocial, behavioral, and health characteristics. That is, the "representativeness" of twin samples (how do they compare with nontwins in sociodemographic characteristics, psychosocial and behavioral factors, health status?), a largely neglected issue, can be directly examined.
Indicative of the kind of studies that need to be carried out is the recent investigation of Fullerton and colleagues (2003). They conducted genome-wide scans for quantitative trait loci (QTLs) that influence variation in the personality trait neuroticism. Such QTLs were identified on chromosomes 1q, 4q, 7p, 12q, and 13q in a population of extremely discordant and concordant sibling pairs. Interestingly, one locus on chromosome 1 is syntenic with that reported from QTL mapping of rodent emotionality (an animal model of neuroticism), suggesting that some animal and human QTLs influencing emotional stability may be homologous. This kind of study could be extended to twins and sibling pairs, where measures of social relationship histories replaced the neuroticism measure. Such investigations could play an important role in understanding the linkages between social relationships, genetics, and, ultimately, neurophysiology and downstream health consequences. Such studies should go well beyond the work of Fullerton and colleagues (2003) to obtain more nuanced characterizations of the diverse environments of twins and siblings. Daily diary studies on persons for whom the QTL assessments had been carried out would be especially valuable.
Moving to more refined biological levels, more research is needed on the mechanistic basis of protection from disease. Illustrative of the kinds of studies that should be promoted is the article by McLaughlin and colleagues (2003), showing that sublethal insults can induce tolerance to subsequent stressors in neurons. In an in vivo model of ischemic tolerance, these authors show that caspase 3 cleavage can occur without cell death in preconditioned tissue. They identify a neuroprotective pathway where events normally associated with apoptotic cell death are, in fact, critical for cell survival. What is missing from this intriguing study is an indication of what kinds of environmental events constitute challenges that are reflected in the preconditioned tissue where caspase 3 cleavage is likely to occur. This is a rich forum for probing linkage between the social environment and consequential protective mechanisms.
Per our opening discussion, we reiterate that susceptibility gene status does not necessarily imply disease manifestation, even in later life. A particularly striking instance of this phenomenon occurs for carriers of APOE4 alleles. In recent studies following people who survive to very old ages, namely, centenarians, it has been found that after age 85, the risk for Alzheimer's disease in APOE4 carriers diminishes sharply (Finch & Kirkwood, 2000). The same sharp reduction in risk after age 85 also holds for carriers of APOE2 and APOE3 genes. Reduced risk of Alzheimer's disease in APOE4 carriers at advanced ages may indicate interactions with other genes and/or environmental influences as yet undocumented but is certainly a result of those individuals who are susceptible to the development of Alzheimer's disease already developing the disease by this age and leaving the remaining population at lower risk. This is a place where in-depth characterizations of the life histories of centenarians, emphasizing their social relationships, could be richly informative. On a more general level, studying healthy centenarians, their genetics, and social environment histories may have major payoff for understanding healthy aging and the protective mechanisms underlying their persistently positive health.
To conclude, developing the interface between genetics, social environments, and health will require close collaboration between those well versed in molecular biology and biochemistry and persons with expertise in genetic epidemiology (e.g., Davey-Smith & Ebrahim, 2003)<--?1-->and social psychology. The rapid rate of discovery of susceptibility genes requires constant attention to the expanding genetic basis of disease and disability in the elderly (see Silander et al. [2004] as one instance of this phenomenon). The complex of susceptibility genes associated with any one disease also places increased emphasis on the need for expanded libraries of whole-genome scans to characterize the nature of susceptibility in different populations. Taking this kind of information to the positive agenda we advocate means that there will be an ever more pressing need for rigorous identification of the environmental influences that protect susceptible persons from disease incidence. Understanding the processes underlying protection will require more than just establishing links to gene expression. It will also demand an ability to identify the chemical responses to social–environmental stimuli. One aspect of this program is the systems biology initiative aimed at understanding the behavior of metabolic networks in response to challenges, both positive and negative (Nicholson & Wilson, 2003; Nicholson, Holmes, Lindon, & Wilson, 2004). This program has the potential to provide critical links between molecular-level genetic characterizations of individuals and biochemical and physiologic responses to diverse social environments. Such an integrated picture of the processes linking positive social experience with protection from disease and disability is the essence of a research agenda we seek to promote.
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gene predicts susceptibility to type-2 diabetes. Diabetes, 53,1141-1149.[Medline]This article has been cited by other articles:
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  Yong Yu, T. Chamorro-Premuzic, and S. Honjo Personality and Defense Mechanisms in Late Adulthood J Aging Health, August 1, 2008; 20(5): 526 - 544. [Abstract] [PDF]
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