SCHRES-05838; No of Pages 7

Schizophrenia Research xxx (2014) xxx–xxx

Contents lists available at ScienceDirect

Schizophrenia Research
journal homepage: www.elsevier.com/locate/schres

Genetic liability, prenatal health, stress and family environment:

Risk factors in the Harvard Adolescent Family High Risk
for Schizophrenia Study
Deborah J. Walder a,b,c,⁎, Stephen V. Faraone d,e, Stephen J. Glatt d,e, Ming T. Tsuang f,g, Larry J. Seidman c,h,⁎⁎
a
Brooklyn College, Department of Psychology, United States
b
The Graduate Center of The City University of New York (CUNY), United States
c
Harvard Medical School, Department of Psychiatry at Beth Israel Deaconess Medical Center, United States
d
SUNY Upstate Medical University, Department of Psychiatry and Behavioral Sciences, United States
e
SUNY Upstate Medical University, Center for Neuropsychiatric Genetics, Biomedical Sciences Program, Neuroscience and Physiology, United States
f
Center for Behavioral Genomics and Institute of Genomic Medicine, Department of Psychiatry at University of California — San Diego, United States
g
Harvard Institute of Psychiatric Epidemiology and Genetics, Harvard School of Public Health, United States
h
Harvard Medical School, Department of Psychiatry at Massachusetts General Hospital, United States

a r t i c l e i n f o a b s t r a c t

Article history: Objectives: The familial (“genetic”) high-risk (FHR) paradigm enables assessment of individuals at risk for schizo-
Received 8 January 2014 phrenia based on a positive family history of schizophrenia in first-degree, biological relatives. This strategy
Received in revised form 6 April 2014 presumes genetic transmission of abnormal traits given high heritability of the illness. It is plausible, however,
Accepted 11 April 2014 that adverse environmental factors are also transmitted in these families. Few studies have evaluated both bio-
Available online xxxx
logical and environmental factors within a FHR study of adolescents.
Methods: We conceptualize four precursors to psychosis pathogenesis: two biological (genetic predisposition,
Keywords:
Stress
prenatal health issues (PHIs)) and two environmental (family environment, stressful life events (SLEs)). Partic-
Psychosis ipants assessed between 1998 and 2007 (ages 13–25) included 40 (20F/20M) adolescents at FHR for schizophre-
Relatives nia (FHRs) and 55 (31F/24M) community controls. ‘Genetic load’ indexed number of affected family members
Obstetric complications relative to pedigree size.
Neurodevelopment Results: PHI was significantly greater among FHRs, and family cohesion and expressiveness were less (and family
Family environment conflict was higher) among FHRs; however, groups did not significantly differ in SLE indices. Among FHRs, genet-
ic liability was significantly associated with PHI and family expressiveness.
Conclusions: Prenatal and family environmental disruptions are elevated in families with a first-degree relative
with schizophrenia. Findings support our proposed ‘polygenic neurodevelopmental diathesis–stress model’
whereby psychosis susceptibility (and resilience) involves the independent and synergistic confluence of
(temporally-sensitive) biological and environmental factors across development. Recognition of biological and
social environmental influences across critical developmental periods points to key issues relevant for enhanced
identification of psychosis susceptibility, facilitation of more precise models of illness risk, and development of
novel prevention strategies.
© 2014 Elsevier B.V. All rights reserved.

1. Introduction disruptions of normal neuromaturational processes (Walker and

Bollini, 2002). Biological susceptibility is reflected in 1) behavioral (fam-
Over the last few decades it has become firmly established that schizo- ily, twin, adoption) genetic studies yielding heritability estimates of
phrenia has early neurodevelopmental origins (Lewis and Murray, 1987; approximately .65–.70 (Gottesman and Shields, 1967), confirmed by na-
Weinberger, 1987) that later manifest in illness expression through tional population-based and registry studies in Denmark (Wray and
Gottesman, 2012) and Sweden (Lichtenstein et al., 2009) and 2) elevated
⁎ Correspondence to: D.J. Walder, Department of Psychology, Rm 5315 James Hall, rates of perinatal complications in schizophrenia (Cannon, Jones et al.,
Brooklyn College, 2900 Bedford Avenue, Brooklyn, NY 11210, United States. Tel.: +1 2002; Cannon, van Erp et al., 2002). Increasingly, molecular genetic ori-
718 951 5000; fax: +1 718 951 4814. gins are being tested with large-scale consortia (Cross-Disorder Group
⁎⁎ Correspondence to: L.J. Seidman, Massachusetts Mental Health Center, 75 Fenwood
of the Psychiatric Genomics Consortium, 2013), pointing to complex
Road, Boston, MA 02115, United States. Tel.: +1 617 754 1238; fax: +1 617 754 1250.
E-mail addresses: DWalder@brooklyn.cuny.edu (D.J. Walder), polygenic influences involving many common single nucleotide variants
lseidman@bidmc.harvard.edu (L.J. Seidman). and rare events such as copy number variants. Perinatal complications

http://dx.doi.org/10.1016/j.schres.2014.04.015
0920-9964/© 2014 Elsevier B.V. All rights reserved.

Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015
2 D.J. Walder et al. / Schizophrenia Research xxx (2014) xxx–xxx

and genetics represent two important risk domains given that they exert aberration) and more social difficulties and reward dependence (Glatt
effects early, impacting brain development. Robust evidence of structural et al., 2006; Rosso et al., 2010), the latter of which were associated
and functional brain abnormalities in nonpsychotic, biological relatives with higher genetic loading (Glatt et al., 2006). We did not report on
between 8 and 30 years of age (Thermenos et al., 2013) supports the no- key environmental variables that may influence these outcomes, such
tion that disrupted neurodevelopment precedes onset of frank psychosis. as perinatal health issues and later life stressors.
For example, gray matter volume abnormalities exist in youth at familial In the present paper, we propose a ‘polygenic neurodevelopmental
high-risk (FHR) compared to controls (Rosso et al., 2010), with greater diathesis–stress model’ that targets four early developmental per-
volume reduction over time associated with increasing symptoms and turbations demonstrated to play a role in psychosis vulnerability in
cognitive deficits in those who develop schizophrenia (McIntosh et al., a temporally-sensitive manner, not previously examined together
2011). Prefrontal cortex alterations and smaller hippocampal volume in a FHR context. We examine two classes of biological precursors (ge-
are the most consistently reported neuroimaging findings in FHR youth, netic predisposition/loading; prenatal health issues (PHIs)) and two
observed in pre-teen, teenage and adult relatives (Boos et al., 2007; classes of social–environmental factors (family environment; stressful
Thermenos et al., 2013). life events (SLEs)) (see Fig. 1).
In contrast to neurobiological studies of schizophrenia patients and Regarding biological precursors, first, prevailing genetic hypotheses
their relatives in family studies, relatively less attention has been paid utilize polygenic models wherein many susceptibility genes of small ef-
to environmental influences, particularly the social environment. Envi- fect (and a few rare genes with larger effects), rather than single major
ronmental factors are emphasized in contemporary conceptualizations genes, predispose to schizophrenia (Gottesman and Shields, 1967). We
of schizophrenia, most prominently in the ‘diathesis–stress’ model utilize a proxy measure of genetic loading (Glatt et al., 2006) to approx-
(Zubin and Spring, 1977). Accordingly, biological vulnerability presum- imate polygenic liability. Second, obstetric complications are one of the
ably interacts with environmental risk toward precipitating psychosis strongest predictors of psychosis risk. Evidence indicates higher rates of
(Tsuang, 2000). Despite high heritability, concordance for schizophre- adverse prenatal events across the psychosis spectrum, such as prenatal
nia in monozygotic twins is only around 0.50 (Cardno and Gottesman, maternal viral exposure, malnutrition, stress, and complications of preg-
2000). This phenotypic discordance implicates environmental factors, nancy and delivery (see Cannon, Jones et al., 2002; Cannon, van Erp
which are important because they are likely more malleable than genet- et al., 2002; Walder et al., 2012). Surprisingly, we are aware of only
ic risk factors, particularly in the context of new approaches to early in- one FHR study that evaluated PHI (Gilbert et al., 2003); accordingly,
tervention and prevention strategies for psychosis. high-risk offspring (compared to controls) had a higher frequency of
Two high-risk paradigms have evolved to identify precursors of psy- birth complications.
chosis. The clinical (or ultra) high-risk paradigm involves ascertainment Stressful life events occurring during development are strongly impli-
of youth with subclinical psychotic symptoms. The FHR approach cated in psychosis risk. Literature demonstrates 1) relationships among
selects nonpsychotic biological relatives to assess liabilities expressed major life events, daily stressors and symptomatology in schizophrenia
across a range of phenotypes presumably reflecting vulnerability. (Norman and Malla, 1993) and 2) social environmental context modu-
Hallmark phenotypes (e.g., odd thinking, smaller hippocampi, stress lates impact of stressful life events (Ventura et al., 1989). Undesirable
sensitivity) can be studied at different ages in FHR studies to evaluate life events are linked with prodromal symptoms, and daily stressors
developmental effects, and in different subpopulations (higher vs. predict increased positive prodromal symptoms (Tessner et al., 2011).
lower genetic loading) to study subgroup expression. The latter ap- Strikingly few studies have examined the influence of stressful life
proach captures an important proportion of individuals at heightened events among youth at FHR for psychosis (Binbay et al., 2012). The
risk while avoiding confounds associated with illness and assumes a one study we are aware of found that social disadvantage increases
cumulative, non-specific, polygenic liability of genetic and environmen- risk more for FHR offspring than non-risk offspring (Wicks et al., 2010).
tal risk factors. Finally, family environment plays a pivotal role in psychosis. Negative
Previously, we demonstrated that compared to controls, Harvard family environment contributes to poor prognosis (Myin-Germeys et al.,
Adolescent FHR youth have neurocognitive difficulties (Seidman et al., 2001) and increases risk independent of family history of psychosis
2006; Phillips et al., 2011; Seidman et al., 2012; Scala et al., 2013), (González-Pinto et al., 2011). Patient exposure to hostile, critical and
more physical anhedonia (but not magical ideation or perceptual emotionally over-involved attitudes by relatives (Lukoff et al., 1984)

Fig. 1. Polygenic neurodevelopmental model.

Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015
 D.J. Walder et al. / Schizophrenia Research xxx (2014) xxx–xxx 3

and high expressed emotion families (Butzlaff and Hooley, 1998) are as- composition. FHRs were significantly older and of lower SES than
sociated with relapse; whereas, low expressed emotion mitigates effects CCs (see Table 1).
of stressful events (Nuechterlein et al., 1994). Family intervention mini- Participants were excluded if they had any lifetime history of psy-
mizing expressed emotion prevents relapse (Leff et al., 1982) and family chotic illness, substance dependence, neurological disease, head injury
interaction style combined with patient symptoms predicts symp- or medical illness with documented cognitive sequelae, sensory impair-
tom relapse (Levene et al., 2009). One unique study found that pa- ments, current psychotropic medication use, or a full-scale IQ estimate
tients managed stressful life events better when perceiving their less than 70 based on eight sub-tests of the third editions of the
families as higher in cohesion, expressiveness, independence and or- Wechsler Intelligence Scale for Children (Wechsler, 1991) or Wechsler
ganization, and lower in conflict (Gretchen-Doorly et al., 2011). Lastly, Adult Intelligence Scale (Wechsler, 1997). CCs were additionally ex-
positive family environment is protective among individuals with a cluded if they had any first- or second-degree biological relative with
family history of psychosis (González-Pinto et al., 2011) and predicts lifetime history of a psychotic disorder.
symptom reduction and increased social functioning among high risk
adolescents (O'Brien et al., 2006), though research on FHR adolescents 2.2. Measures and procedures
is scarce.
In the present study we hypothesized that, compared to community After probands gave consent, their children and siblings were
controls, FHRs would demonstrate 1) greater PHI and SLEs, 2) greater contacted to determine eligibility and willingness to participate. Partic-
family conflict and less family cohesion, 3) differences in expressiveness ipants age 18 years and older gave informed consent. Subjects younger
and 4) a significant relationship of genetic liability with early (PHI) and than 18 years gave assent in conjunction with parental informed
later (SLE; family environment) developmental factors. consent. Subjects received payment for participation. The study was ap-
proved by the human research committees of Massachusetts Mental
Health Center, Massachusetts General Hospital and Harvard Medical
2. Methods School.

2.1. Sample 2.2.1. Diagnostic assessment

Probands were administered several measures to screen for psycho-
The current sample was ascertained as part of the Harvard Adoles- sis, substance use, mood disturbance and other inclusion and exclusion
cent FHR study between 1998 and 2007, described previously in detail criteria. Measures included the Psychosis, Substance Abuse and Mood
(Glatt et al., 2006; Seidman et al., 2012). The analyses herein are Disorders modules of the Washington University Kiddie Schedule for
novel, as are group comparisons on PHI, FE and SLE. Participants Affective Disorders and Schizophrenia (Geller et al., 1994), the DIGS,
13–25 years of age consisted of two groups; biological offspring and and the Neurodevelopmental Questionnaire (Faraone et al., 1995). For
siblings of schizophrenia probands (FHRs), and a community control all measures, higher scores reflect greater risk, more severe symptom-
(CC) group who were the biological offspring and siblings of control atology or poorer functioning, except Youth Self Report — Competence
probands. FHRs included 40% offspring and 60% siblings of 31 families for Activities scale upon which a higher score reflects better functioning.
with adult probands (at least 18 years of age) who met the DSM-IV
criteria (American Psychiatric Association, 1994) for schizophrenia 2.2.2. Measures of early biological and environmental susceptibility
(n = 25) and schizoaffective, depressed type (n = 6). There were The FIGS was administered to parents to assess family history of psy-
11 families with parent–offspring data. Ten of these 11 families had chiatric illness and to derive a genetic liability index. The ‘genetic load’
1 proband parent; 6 fathers and 4 mothers. One of these 11 families index (or incremental degree of presumed genetic risk) was derived
had 2 proband parents; 1 father and 1 mother. The CCs from 35 fam- based on the ‘allele-sharing’ method to compute the relative proportion
ilies consisted of children of parents diagnosed according to the of alleles individuals are expected to share with their affected biological
DSM-IV criteria with no mental illness (n = 25), major depressive relatives versus unaffected biological relatives, while accounting for
disorder (n = 8), mood disorder due to a general medical condition the overall pedigree size. Similar to relative risk and genetic liability
(n = 1), or cannabis abuse (n = 1), using the Diagnostic Interview methods, this method assumes a tight correspondence between traits
for Genetic Studies (DIGS; Nurnberger, 1994) and Family Interview under study and risk genes for schizophrenia. Values of genetic loading
for Genetic Studies (FIGS; Maxwell, 1992). FHR and CC groups were using this model ranged from 0 to 1, with higher values reflecting greater
comparable on sex distribution, educational level and ethnic genetic loading (Glatt et al., 2006).

Table 1
Demographic characteristics of the control and familial high risk groups.

Group Group difference

Community control (n = 55) Familial high risk (n = 40)

Sex (N)
Male 24 20 X2(1) = .5, p = .68
Female 31 20
Mean age (SD) 17.2 (3.7) 19.4 (3.9) t(93) = −2.9, p = .005**
Education 11.0 (3.3) 11.4 (2.7) t(93) = −.6, p = .55
SESa 48.1 (15.5) 38.0 (16.4) t(90) = 3.0, p = .003**
Ethnicity (N)
Caucasian 34 23 X2(5) = 6.0, p = .30
African American 6 7
Hispanic, Caucasian 9 8
Hispanic, Black 5 0
Asian 1 1
Portuguese, Cape Verdean 0 1

SES = socioeconomic status based on Hollingshead, 1975.

**p b .01, *p b .05; two-tailed tests.
a
n = 92.

Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015
4 D.J. Walder et al. / Schizophrenia Research xxx (2014) xxx–xxx

The Pregnancy History Instrument — Revised (Buka et al., 2004) is a 3. Results

brief structured interview administered to mothers designed to obtain
pregnancy and neonatal history. Items cover events related to maternal 3.1. Normality testing
history, pregnancy, delivery and the neonatal period. An index of prena-
tal health issues (PHIs) was calculated by summing all endorsed items All measures were normally distributed with exception of SLE-
corresponding to the prenatal period. PHI included, for example, infec- Impact, which became normally distributed after applying the Box–
tions, gestational, placental, maternal weight, cardiovascular, immuno- Cox transformation.
logical/endocrinological, neurological and psychiatric problems, RH
incompatibility, thyroid disorder, exposure to x-rays and maternal 3.2. Group differences in predictor variables
smoking. There were a total of 25 prenatal items, yielding a maximum
total raw score of 25. PHI, but not SLE-Total or SLE-Impact, was significantly greater
among FHRs than CCs. Patterns of family interaction differed such that
2.2.3. Measures of stress and family environment Cohesion and Expressiveness were significantly less among families of
The Adolescent Life Change Event Scale (Yeaworth et al., 1980), a FHRs compared to CCs, whereas Conflict was non-significantly higher
self-report measure, was administered to assess adverse, stressful life in FHRs (p = .07). Findings remained significant for PHI, FES-Cohesion
events (SLEs). Two indices were derived. First, Total Number of Life and FES-Expressiveness (though non-significant for the SLE indices)
Events (SLE-Total) included number of life events experienced by the after controlling for both age and SES. Findings became significant for
adolescent in the past 6 months (27 items) (e.g., failing one or more FES-Conflict after controlling for both age and SES (p b .001) (see
subjects in school), plus the number of four significant events experi- Table 2). Among FHRs alone and CCs alone, 34 (85%) and 50 (90.9%) ex-
enced by the adolescent ever (i.e., death of a parent, brother or sister, perienced at least one SLE, and 20 (50%) and 36 (65%) experienced at
or close friend), yielding a maximum total raw score of 31. Second, an least one PHI, respectively.
Impact (or total life change unit; SLE-Impact) score was computed,
which weighted the 31 events based on severity, according to a
predetermined rank-order scale (least to most upsetting events). The 3.3. Associations of genetic liability with early biological–environmental
Impact score was the sum of the scores for each event experienced. precursors and later environmental stress factor within the FHR group
The three scales underlying the relationship dimension of the Family
Environment Scale — Form R-Current (FES) (Moos and Moos, 1994), Genetic liability was significantly positively associated with PHI
a self-report questionnaire, were administered to measure current and FES-Expressiveness, though not with SLE-Total, SLE-Impact,
(within the last 6 months) social and environmental characteristics of FES-Cohesion or FES-Conflict (Table 3). After adjusting for SES and
the family, based on individuals' perceptions of their actual family envi- age, correlations of genetic liability with PHI and FES-Expressiveness
ronments. The three relationship dimensions included Cohesion, Ex- remained significant, and SLE indices, FES-Cohesion and FES-Conflict
pressiveness and Conflict. This measure was administered primarily to remained non-significant.
a caregiver/parent of the adolescent in 56 families and, when not avail-
able in five families, self-report from the adolescent was used. Data 4. Discussion
were missing for five families.
As hypothesized, adolescents at FHR for psychosis differed signifi-
2.3. Statistical analyses cantly from comparisons regarding a number of biological and environ-
mental risk factors from conception through young adulthood. Most
Independent sample t-tests were employed to examine group dif- markedly, prenatal health issues and family conflict were significantly
ferences (FHR vs. CC) in continuously distributed demographic vari- greater, whereas family cohesion and expressiveness were significantly
ables, including age, education and parental SES. Chi-square tests less among FHRs. Among FHR adolescents, greater genetic liability was
were employed to assess group differences in sex and ethnicity. Inde- associated with more prenatal health issues and family expressiveness.
pendent sample t-tests were employed to examine group differences The number of stressful life events was somewhat (albeit non-
in predictors. Pearson bivariate correlations were employed to examine significantly) greater among FHR families. Overall, these data indi-
relationship of genetic load with PHI, SLE, and FES indices. Given group cate that biological and social environmental risk factors are impor-
differences in age and SES, analyses were repeated controlling for age tant within FHR families. Our finding that greater genetic liability is
and SES, using ANCOVA (for the PHI index), MANCOVA (for the SLE associated with greater family environment disruption fits a cumulative
and FES indices, respectively) and partial correlations. All tests were exposure (or “behavioral sensitization”) (see van Winkel et al., 2008)
two-tailed. model of psychosis risk.

Table 2
Means, standard deviations, effect sizes (Cohen's D) and group differences in precursors of psychosis susceptibility as a function of familial risk.

Group Cohen's Da Group difference Group difference covaried for age & SES

Community control Familial high risk

Prenatal health issuesb (n = 45;23) 1.7 (1.4) 3.3 (2.6) −0.86 t(28.4) = −2.7, p = .01* F(3) = 6.8, p b .001***
Stressful life eventsc
Total score (n = 55;39) 2.9 (1.8) 3.3 (2.5) −0.19 t(92) = −.98, p = .33 F(3) = .30, p N .10
Impact factord (n = 55;40) 138.9 (111.8) 202.8 (170.8) −0.46 t(93) = −1.9, p = .06 F(3) = 1.9, p N .10
Family Environment Scale
Cohesion (n = 55;34) 58.9 (12.2) 46.0 (16.6) 0.93 t(54.9) = 3.9, p b .001*** F(3) = 8.5, p b .001***
Expressiveness (n = 55;35) 56.4 (12.1) 48.3 (12.1) 0.75 t(88) = 3.1, p b .005** F(3) = 4.1, p b .01**
Conflict (n = 55;35) 44.3 (11.0) 48.7 (10.8) −0.41 t(88) = −1.9, p = .07 F(3) = 6.6, p b .001***

*p b .05; **p b .01; ***p b .001; all tests are two-tailed.

a
Cohen's D = [(CCMean − FHRMean) / sqrt S2pooled] based on unadjusted data.
b
Pregnancy History Instrument — Revised.
c
Adolescent Life Change Event Scale.
d
Box–Cox transformed data.

Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015
 D.J. Walder et al. / Schizophrenia Research xxx (2014) xxx–xxx 5

Table 3 between individuals within families who participated and those who
Pearson bivariate correlations among biological and environmental predictors among did not. Also, the family environment stress measure was administered
adolescents at familial high-risk.
primarily to a caregiver/parent of the adolescent (~80% of the sample)
Genetic liability index or, when not available, to the adolescent. Adolescents may have differ-
Prenatal health issuesa (n = 66) .49 (n = 21) ent perceptions of stressful life events in the family environment not
(.03)* accounted for in the current study, rendering this an important consid-
Stressful life eventsb eration for future investigation. In addition, unaffected relatives of
Total score (n = 89) .17 (n = 34)
control probands (some of whom carried a history of depression, for
(.35)
c
Impact factor (n = 89) .03 (n = 34) example) were included to avoid a ‘supernormal’ control group; this
(.85) may have reduced the magnitude of group differences (see Seidman
Family Environment Scale et al., 2006) and limited generalizability. Significant group differences
Cohesion (n = 85) .06 (n = 30) despite this selection strategy, however, render results all the more
(.77)
striking. Similarly, findings after corrections for differences in family
Expressiveness (n = 86) .41 (n = 31)
(.02)* SES remained significant.
Conflict (n = 86) .07 (n = 31) The PHI measure may have been subject to maternal recall bias.
(.72) However, prior studies assessing the current PHI measure demonstrated
*p b .05; **p b .01; ***p b .001; all tests are two-tailed. no evidence of positive maternal recall bias (Buka et al., 2000), or inaccu-
a
Pregnancy History Instrument — Revised. racy was limited to certain types of PHI (Buka et al., 2004). Our study in-
b
Adolescent Life Change Event Scale. cluded prenatal factors that extended beyond those identified by Buka
c
Box–Cox transformed data.
et al. (2004) as particularly susceptible to recall bias. Thus, positive recall
bias may not likely play a significant role in the current study, bolstering
Finally, our finding that high risk families are marked by a more con- confidence in the current interpretation of findings. Nonetheless, research
flict-laden and less cohesive style of family interaction, coupled with ge- data drawn from current perinatal observation is necessary to confirm
netic liability being associated with a more highly expressive family this finding. Although at least 50% of the FHRs and CCs each experienced
pattern, is consistent with the notion that having a first-degree family at least one SLE and/or one PHI, the mean occurrences of SLEs (CC =
member increases likelihood of a “risky family” environment. In turn, 2.9(1.8); FHR = 3.3(2.5)) and PHIs (CC = 1.7(1.4); FHR = 3.3(2.6))
chronically stressful family environments – marked by conflict, defi- were relatively low. Thus, despite restricted statistical power, detection
cient nurturing, harshness, neglect or aggression – may serve as a risk of significant group differences for PHIs was all the more striking; limit-
precursor for adverse health outcomes via allostatic load (Repetti ed power may partly account for the absence of significant findings
et al., 2011). Moreover, social networks of recently diagnosed schizo- among SLE data. Finally, although we assessed 3 categories of outcomes
phrenia patients tend to be smaller and marked by relatively more fam- (6 variables) raising the risk of Type 1 error, all would be significant
ily members than other families (Horan et al., 2006). Such social with Bonferroni correction by category of measure.
network discrepancies underscore the family environment as important The current study supports the early components of our proposed
for patients in managing illness (Gretchen-Doorly et al., 2011). Specifi- ‘polygenic neurodevelopmental diathesis–stress model’ (Fig. 1) where-
cally, the family social environment (beyond familial genetic vulnerabil- by psychosis susceptibility (and resilience) involves the independent
ity) may modulate stress effects (Ventura et al., 1989). and synergistic incremental confluence of biological and environmental
Inferences about causal directionality of effects are made cautiously. factors, in a temporally sensitive (and potentially dependent) manner
Genetic liability contributes to individual differences (e.g., inherent across important developmental periods. Arguably, the more (crucial)
traits/personality) that impact likelihood of exposure to environmental sensitive windows include prenatal through adolescence, given promi-
adversities (Rutter et al., 2001). Moreover, having a family member nent neuromaturational processes (e.g., apoptosis, synaptic pruning,
with psychiatric illness may increase the likelihood of stressful life synaptogenesis, neural/cellular migration, neurohormonal surges) dur-
event exposure. In addition, genetic effects on behavior may emerge ing these periods, which may affect target features and neuropatholog-
via individual likelihood of experiencing environmental adversities ical signs of risk and illness.
involving psychosocial stress and family environment (see van The currently employed multivariate approach draws attention to a
Winkel et al., 2008). Genetic liability and environmental stress also vicissitude of mechanisms for future investigation, by which biological
may modulate outcome (Brown, 2011), as evidenced in the Finnish and environmental influences may converge toward enhancing identi-
Adoptive Family Study (Tienari et al., 2004). Genes also influence hy- fication of putative psychosis susceptibility. First, our findings support
pothalamic–pituitary–adrenal axis sensitivity (Walder et al., 2010), the possibility that genetic liability is linked with increased risk of
the primary neural system implicated in the biological stress response, obstetric complications among offspring. It remains unclear whether
magnifying stress impact. This follows Walker & Diforio's (1997) neural greater PHI is due to greater risk of adverse pregnancy among mothers
diathesis–stress model, positing hypothalamic–pituitary–adrenal axis as with schizophrenia (psychological distress) (Sacker et al., 1996), or ge-
a plausible candidate neurobiological substrate regulating susceptibility netic liability brings its own direct risk to fetal development. Evidence
toward psychosis via sensitization of striatal pathways/dopaminergic points to familial vulnerability for perinatal stress and schizophrenia
neurotransmission. (see Walder et al., 2012) including a 5-fold increased schizophrenia
This study offers a unique window to understanding individual risk among individuals with prenatal infection exposure and positive
effects of genetic predisposition, early prenatal factors and later en- family history of psychosis (Clarke et al., 2009). Genetic liability may
vironmental influences on psychosis vulnerability from a developmen- enhance sensitivity to (or modulate) prenatal complications toward
tal perspective. Findings accentuate the need for research aimed at heightened illness susceptibility and expression (Jablensky et al., 2005).
disentangling the biological ‘synergism’ versus ‘parallelism’ debate The case–control design does not distinguish mechanisms via which hav-
(see Darroch, 1997). That is, elucidating the complex, variable pathways ing a first-degree relative with psychosis impacts pre- and post-natal de-
to psychosis risk paved by the interplay of genes and environment via velopmental factors, with full consideration of rGE and GxE explanations.
(multiplicative and/or additive) interaction (GxE; see van Winkel Although precise mechanisms remain unclear, there is mounting evi-
et al., 2008) and/or covariation (rGE) remains crucial. dence of ‘early life programming’ (Bale et al., 2010), whereby PHI-
Study limitations include data loss on some variables (such as prena- related perturbations may alter neurodevelopment during a critical pe-
tal complications and FES) and substantial variability in stress measures. riod of heightened sensitivity with prominent downstream effects. This
Moreover, we could not determine whether there were any differences is one possible explanation of the origin of neuroanatomic

Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015
6 D.J. Walder et al. / Schizophrenia Research xxx (2014) xxx–xxx

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Role of funding source
U. S. A. 58, 199–205.
This work was supported by the following: Fellowship Leave, The City University of
Gretchen-Doorly, D., Detore, N.R., Ventura, J., Hellemann, G., Subotnik, K.L., Nuechterlein,
New York (DJW); Stanley Medical Research Institute (LJS); National Association for K.H., 2011. Relationships between perceptions of the family environment and of neg-
Research on Schizophrenia and Depression (NARSAD; LJS, MTT); Mental Illness and ative life events in recent-onset schizophrenia patients. Schizophr. Res. 127,
Neuroscience Discovery (MIND) Institute (LJS); MH 43518 and MH 65562 (MTT, LJS); 266–267.
MH 63951 (LJS); MH 46318 (MTT); The Commonwealth Research Center of the Haavik, J., Halmøy, A., Hegvik, T., Johansson, S., 2011. Maternal genotypes as predictors of
Massachusetts Department of Mental Health, SCDMH82101008006 (LJS). offspring mental health: the next frontier of genomic medicine? Futur. Neurol. 6,
731–743.
Contributors Hollingshead, A.B., 1975. Four factor index of social status. Yale University Department of
Sociology, New Haven, CT.
Authors LJS, SVF and MTT designed the overarching study and protocol and received
Horan, W.P., Subotnik, K.L., Snyder, K.S., Nuechterlein, K.H., 2006. Do recent-onset schizo-
funding. LJS supervised all data collection. SVF supervised statistical analyses. SJG contrib-
phrenia patients experience a “social network crisis”? Psychiatry 69, 115–129.
uted statistical approaches. DJW generated the current study hypotheses and model,
Jablensky, A.V., Morgan, V., Zubrick, S.R., Bower, C., Yellachich, L.-A., 2005. Pregnancy,
conducted the literature search/review and statistical analyses, and wrote the first draft delivery, and neonatal complications in a population cohort of women with schizo-
of the manuscript. All authors contributed to the contents of the manuscript and approved phrenia and major affective disorders. Am. J. Psychiatry 162, 79–91.
the final manuscript. Leff, J., Kuipers, L., Berkowitz, R., Eberlein-Vries, R., Sturgeon, D., 1982. A controlled trial of
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Please cite this article as: Walder, D.J., et al., Genetic liability, prenatal health, stress and family environment: Risk factors in the Harvard
Adolescent Family High Risk for Schizophrenia Study, Schizophr. Res. (2014), http://dx.doi.org/10.1016/j.schres.2014.04.015