Neurocognitive performance in family-based and case-control studies of schizophrenia
Introduction
Methods of ascertainment are pivotal across biomedical research and are an important consideration in the research design. In genetic studies, the utility and statistical approach of family-based and unrelated case-controls studies has been discussed (e. g. Hiekkalinna et al., 2012). The incorporation of endophenotypes to genetic investigations of schizophrenia (SZ) has grown significantly with neurocognitive measures (Gur et al., 2007a, Gur et al., 2007b, Lee et al., 2015--in this issue, Nuechterlein et al., 2015--in this issue, Stone et al., 2015--in this issue) and neurophysiological measures (Swerdlow et al., 2014, Light et al., 2015--in this issue, Turetsky et al., 2015--in this issue) playing key roles. Family-based designs enable testing the endophenotype criteria (Braff et al., 2007, Braff, 2015--in this issue, Gottesman and Gould, 2003) and, when sufficiently powered, allow for the examination of heritability, association with the disease phenotype and co-segregation within families (Glahn et al., 2014, Greenwood et al., 2007, Greenwood et al., 2011, Greenwood et al., 2013).
Several meta-analyses have reported that adult relatives of probands with SZ show intermediate deficits in neurocognitive measures including executive functions, such as working memory and attention, verbal fluency and sensori-motor speed (Faraone et al., 2001, Kremen and Hoff, 2004, Sitskoorn et al., 2004, Snitz et al., 2006). Similar deficits have also been observed in younger relatives (Niemi et al., 2003, Seidman et al., 2006, Keshavan et al., 2010, Agnew-Blais and Siedman, 2013). The neurocognitive domains implicated in family-based studies are similar to deficits observed in case-control studies (Gur et al., 2001b). Yet, direct evaluation of these complementary ascertainment strategies applying the same measures has not been conducted. The Penn computerized neurocognitive battery (CNB) used in the Consortium on the Genetics of Schizophrenia (COGS) provides a unique opportunity to evaluate effects of ascertainment methods—family-based (COGS-1) vs. case control (COGS-2)—with the same neurocognitive battery across the participating sites.
The CNB, developed in concert with functional neuroimaging studies (Gur et al., 2010), has been validated in healthy participants and people with SZ (Gur et al., 2001a, Gur et al., 2001b) and is sensitive to the effects of age and sex (Gur et al., 2012, Irani et al., 2012). The battery, which provides measures of performance accuracy and response time, was applied in three independent large-scale family-based genetic studies. The Multiplex Multigenerational Investigation of Schizophrenia (MGI; Gur et al., 2007a) reported that probands demonstrated greatest impairment relative to healthy controls, with intermediate performance of family members. Liability for SZ affected the speed–accuracy tradeoff differently for specific neurocognitive domains. Significant heritability estimates were obtained for accuracy of verbal, facial, and spatial memory and spatial and emotion processing. For speed, estimates of heritability were significant for abstraction and mental flexibility, attention, face memory, and spatial and sensorimotor processing. The results of the Project among African-Americans to Explore Risks for Schizophrenia (PAARTNERS) revealed that patients with SZ exhibited less accuracy and speed in most neurocognitive domains than their relatives, who were impaired relative to HCS in most domains. Significant heritabilities were observed for most neurocognitive domains, with the highest for accuracy of abstraction and mental flexibility, verbal memory, face memory, spatial processing, and emotion processing and for speed of attention (Calkins et al., 2010).
In COGS-1 all of the measures applied from the Penn CNB (Abstraction and Mental Flexibility, Face Memory, Spatial Memory, Spatial Processing, Sensorimotor Dexterity, and Emotion Recognition) were significantly heritable with heritability estimates ranging from 24% for Spatial Memory to 55% for Spatial Processing (Greenwood et al., 2007). These heritabilities are in the same range as the heritability of SZ itself in the COGS-1 families (Light et al., in press). Furthermore, we noted sex differences in familiality effects with male probands' performance predictive of performance of their unaffected relatives (Calkins et al., 2013). The subsequent application of the CNB in the case-control design of COGS-2 enabled evaluation of the pattern of performance of individuals with SZ, compared to HCS, ascertained in family-based and case-control designs. We noted that in some endophenotypic measures in COGS-1 probands were less impaired than observed in other samples of patients with SZ (Greenwood et al., 2007). The major ascertainment difference between the samples is that patients recruited for COGS-1 required the availability of parents and siblings while COGS-2 permitted participation of patients regardless of family availability (Swerdlow et al., 2015--in this issue). This difference likely affects multiple demographic characteristics related to age, education, socioeconomic status as well as severity of illness, favoring COGS-1. We hypothesized that while the profile of impairment would be similar, probands in the COGS-1 family-based ascertainment would perform better than those ascertained as cases in COGS-2.
Section snippets
Participants
Details on the COGS-1 and COGS-2 samples' ascertainment, inclusion and exclusion criteria and clinical assessment are provided elsewhere in this issue (Braff et al.; Swerdlow et al.). Briefly, COGS-1, a family-based design, and COG-2, a case-control design, included probands 18–65 years old who met DSM-IV criteria for schizophrenia based on established diagnostic procedures. COGS-1 required that both biological parents were available for genotyping, and that at least one full sibling,
Performance comparisons on the computerized neurocognitive battery
The means and standard deviations, as well as p values for Student's t-tests and effect sizes comparing patients and controls within each sample and between samples are presented in the bottom portion of Table 1. The z-scores of patients compared to their respective control groups are illustrated in Fig. 1.
As can be seen in Table 1, both COGS-1 patients and COGS-2 patients are impaired relative to their respective controls, although the effect sizes range from small to moderate in COGS-1, with
Discussion
The Consortium on the Genetics of Schizophrenia (COGS) allowed for the comparison of neurocognitive performance deficits between individuals with schizophrenia ascertained through a family-based sampling (COGS-1) and those ascertained through case-control sampling (COGS-2) with their differing ascertainment strategies as discussed above and in this issue (cf. Swerdlow et al., 2015--in this issue). The results indicated very similar neurocognitive deficit profiles, for COGS-1 and COGS-2
Role of funding source
This work was supported by collaborative R01 grants from the National Institute of Mental Health. COGS-1 and COGS-2: MH065571 UCSD, MH065707 UCLA, MH065554 MSSM, MH065578 Penn, MH065558 Washington; COGS-1 Only: MH065588 Colorado, MH065562 Harvard; Seidman and Stone are on a subcontract for COGS-2; COGS-2 Only: MH86135 Stanford.
Contributors
All authors significantly contributed to study design, data collection and reviewed and approved this manuscript.
Conflict of interest
Dr. Green has been a consultant to AbbVie, Biogen, DSP, EnVivo/Forum and Roche, and he is on the scientific advisory board of Mnemosyne. He has received research funds from Amgen. Dr. Lazzeroni is an inventor on a patent application filed by Stanford University on genetic polymorphisms associated with depression. Dr. Light has served as a consultant for Astellas, Forum, and Neuroverse. Dr. Nuechterlein has received unrelated research support from Janssen Scientific Affairs, Genentech, and Brain
Acknowledgments
We thank the research staff who administered the CNB, Allison Mott CNB Implementation Manager, University of Pennsylvania and the patients, families and healthy volunteers who participated in the study.
References (43)
The importance of endophenotypes in schizophrenia research: past, present and future
Schizophr. Res.
(2015)- et al.
Sex differences in familiality effects on neurocognitive performance in schizophrenia
Biol. Psychiatry
(2013) - et al.
More than just tapping: index finger-tapping measures procedural learning in schizophrenia
Schizophr. Res.
(2012) - et al.
Computerized neurocognitive scanning: I. Methodology and validation in healthy people
Neuropsychopharmacology
(2001) - et al.
Computerized neurocognitive scanning: II. The profile of schizophrenia
Neuropsychopharmacology
(2001) - et al.
A cognitive neuroscience-based computerized battery for efficient measurement of individual differences: standardization and initial construct validation
J. Neurosci. Methods
(2010) - et al.
The modified global assessment of functioning scale: addendum
Psychosomatics
(1995) - et al.
Computerized neurocognitive test performance in schizophrenia: a lifespan analysis
Am. J. Geriatr. Psychiatry
(2012) - et al.
Verbal working memory in schizophrenia: the moderating role of smoking status and antipsychotic medications
Schizophr. Res.
(2015) - et al.
Validation of mismatch negativity and P3a for use in multi-site studies of schizophrenia: characterization of demographic, clinical, cognitive, and functional correlates in the COGS-2
Schizophr. Res.
(2015)
Childhood developmental abnormalities in schizophrenia: evidence from high-risk studies
Schizophr. Res.
Attention/vigilance in schizophrenia: performance results from a large multi-site study of the Consortium on the Genetics of Schizophrenia (COGS)
Schizophr. Res.
Cognitive deficits in relatives of patients with schizophrenia: a meta-analysis
Schizophr. Res.
California Verbal Learning Test-II performance in schizophrenia as a function of ascertainment strategy: Comparing the first and second phases of the Consortium on the Genetics of Schizophrenia (COGS)
Schizophr. Res.
Deficient prepulse inhibition in schizophrenia detected by the multi-site Consortium on the Genetics in Schizophrenia
Schizophr. Res.
Consortium on the Genetics of Schizophrenia (COGS) assessment of endophenotypes for schizophrenia: an introduction to this special issue of Schizophrenia Research
Schizophr. Res.
The utility of P300 as a schizophrenia endophenotype and predictive biomarker: Clinical and socio-demographic modulators in COGS-2
Schizophr. Res.
Neurocognition in youth adults under age 30 at familial risk for schizophrenia: a quantitative and qualitative review
Cogn. Neuropsychiatry
Scale for the Assessment of Negative Symptoms (SANS)
Scale for the Assessment of Positive Symptoms (SAPS)
Deconstructing schizophrenia: an overview of the use of endophenotypes in order to understand a complex disorder
Schizophr. Bull.
Cited by (31)
Familial risk of psychosis in obsessive-compulsive disorder: Impact on clinical characteristics, comorbidity and treatment response
2022, Journal of Psychiatric ResearchCitation Excerpt :As dysfunction in the cortico-striato-thalamic circuitry is postulated to be a key mechanism in both disorders, there is also substantial overlap in the endophenotypes identified between them. For example, many studies in OCD have reported working memory deficits, which is considered a key endophenotype in schizophrenia (Abramovitch et al., 2015; Gur et al., 2015). Aberrations in certain neurophysiological measures such as evoked potentials (P300, mismatch negativity, etc.) are common to both disorders.
Comparison of two cognitive screening measures in a longitudinal sample of youth at-risk for psychosis
2022, Schizophrenia ResearchCitation Excerpt :Cognitive impairment is most evident in patients with chronic symptoms of psychosis, however, multiple studies report cognitive deficits in first-episode psychosis patients (FEP) (Sawada et al., 2017; Saykin, 1994; Simon et al., 2007), in those at clinical high-risk (CHR) for developing psychosis (Bolt et al., 2019; De Herdt et al., 2013; Gur et al., 2015a; Lencz et al., 2006; Reichenberg, 2005; Zhang et al., 2021a), and in those with sub-threshold psychosis spectrum (PS) symptoms (Gur et al., 2014; Gur et al., 2015b).
Deviation from expected cognitive ability is a core cognitive feature of schizophrenia related to neurophysiologic, clinical and psychosocial functioning
2020, Schizophrenia ResearchCitation Excerpt :Further, deviation scores accounted for the largest shared variance when predicting illness duration (R2 = 0.012 vs. 0.003) (see Fig. 3). Cognitive impairment is a key characteristic of schizophrenia due to its prevalence, severity, and relationship to major domains of neurophysiologic, clinical, and psychosocial function (Green et al., 2004; Gur et al., 2015; Hill et al., 2013; Hochberger et al., 2016; Light et al., 2012; Perry et al., 2000; Rissling et al., 2014; Swerdlow et al., 2015; Thomas et al., 2017). Neuropsychological assessment based on population-based norms remains the gold standard for evaluating current cognitive functioning in schizophrenia and other disorders (Crawford, 2005; Kessels and Hendriks, 2015; Lezak, 1995).
Performance on a computerized neurocognitive battery in 22q11.2 deletion syndrome: A comparison between US and Israeli cohorts
2016, Brain and CognitionCitation Excerpt :This is also true in the 22q11DS field and there is an on-going effort to harmonize assessments across multiple sites through the International 22q11.2 Brain Behavior Consortium. Notably, because PCNB has been used in other relevant populations including clinical high risk for psychosis and family members of schizophrenia (R.C. Gur et al., 2014, 2015), use of PCNB in 22q11DS should allow a comparison across multiple at-risk populations. In the present study, we have administered a Hebrew translation of the PCNB to a 22q11DS cohort in Tel Aviv (TLV), Israel and compared their neurocognitive profile to one of the largest 22q11DS cohorts based in Philadelphia (PHL), United States.