Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, 'missing' heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

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Finding the missing heritability of complex diseases

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

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Biological insights from 108 schizophrenia-associated genetic loci

Schizophrenia is a severe mental disorder with a lifetime risk of about 1%, characterized by hallucinations, delusions and cognitive deficits, with heritability estimated at up to 80%(1,2). We performed a genome-wide association study of 3,322 European individuals with schizophrenia and 3,587 controls. Here we show, using two analytic approaches, the extent to which common genetic variation underlies the risk of schizophrenia. First, we implicate the major histocompatibility complex. Second, we provide molecular genetic evidence for a substantial polygenic component to the risk of schizophrenia involving thousands of common alleles of very small effect. We show that this component also contributes to the risk of bipolar disorder, but not to several non-psychiatric diseases.

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Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Age-related macular degeneration (AMD) is a major cause of blindness in the elderly. We report a genome-wide screen of 96 cases and 50 controls for polymorphisms associated with AMD. Among 116,204 single-nucleotide polymorphisms genotyped, an intronic and common variant in the complement factor H gene ( CFH ) is strongly associated with AMD (nominal P value -7 ). In individuals homozygous for the risk allele, the likelihood of AMD is increased by a factor of 7.4 (95% confidence interval 2.9 to 19). Resequencing revealed a polymorphism in linkage disequilibrium with the risk allele representing a tyrosine-histidine change at amino acid 402. This polymorphism is in a region of CFH that binds heparin and C-reactive protein. The CFH gene is located on chromosome 1 in a region repeatedly linked to AMD in family-based studies.

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Complement Factor H Polymorphism in Age-Related Macular Degeneration

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

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LD score regression distinguishes confounding from polygenicity in genome-wide association studies :

The theme of this volume that psychiatry and neuropsychology be systematically aligned with the neurophenotype approach in order to facilitate a systems-level understanding of brain–behavior relationships is reiterated across chapters. This chapter outlines a few conceptual and programmatic adjustments that these disciplines must undertake in order to promote that goal. Firstly, this chapter argues that the historically influential endophenotype concept must be constrained that it has been applied by default to cognitive and neural markers without adequate consideration of the host of variables that modulate neural systems tied to cognition. In this regard, it is also argued that the broader neurophenotype concept has greater utility. Secondly, the need for refinement of cognitive and behavioral constructs is stressed; how ontologies for cognitive and neural processes serve this end is discussed. Thirdly, the imperative that psychiatry and neuropsychology adopt data formats that facilitate data integration in genome–phenome mapping systems is emphasized. And to illustrate the point, a few pioneering examples of knowledge discovery and neuroinformatics platforms that relate to these disciplines are described.

Conclusion: Implications for Psychiatry and Neuropsychology

This chapter provides a critical appraisal of the concept of a circuit-centered neurophenotype that is conceptualized within a genome-to-phenome framework. Representing many of the kinds of variables that complicate this model are a few select ones that are sampled in this chapter. They include the following: (a) The problem of minimal circuit definition—the many scales of neural circuitry and the difficulty of demarcating circuits within some forms of neural architecture; (b) the modulation of neural circuits and the alterations of circuit architecture through non-gene-regulated factors such as synaptic plasticity, extra-synaptic neuromodulation, and bioelectric dynamics; and (c) technical and methodological considerations in circuit delineation—as is coming to light in the field of microscale connectomics. Adding these complex variables from neuroscience into the fray make for great attenuation of the notion of a circuit neurophenotype in the behavioral neurosciences, and this is given some depth of coverage in this chapter. However, the chapter does not dismiss the utility of the concept of circuit neurophenotypes. It concludes with a discussion of the kinds of additional information that may be needed in order for the concept to be better validated.

Appraising Circuit-Centered Neurophenotypes

This introductory chapter provides a summary description of key developments in the neurosciences and biomedical sciences that have compelled the topic of the volume—neural and cognitive markers. The emergence of “omics” disciplines is described—where large or complex data sets are deciphered with bioinformatics methods in a systems biology framework. The developments of phenomics in the context of genome-to-phenome mapping, connectomics in neuroscience, and Research Domain Criteria in psychiatry are then staged, as is the current research-scientific environment, characterized by data repositories and knowledge discovery systems. The central point converged upon is that the impact of systems biology necessitates that the clinical and behavioral neurosciences delineate cognitive and neural systems in a manner that can be integrated with broader scientific frameworks. This chapter also explains the volume’s adoption of the umbrella term “neurophenotype” and provides an operating definition of the term. The two-part structure of the volume is then laid out with the topic of each chapter summarized.

Introduction and Structure of the Volume

Background While COVID-19 vaccines reduce adverse outcomes, post-vaccination SARS-CoV-2 infection remains problematic. We sought to identify community factors impacting risk for breakthrough infections (BTI) among fully vaccinated persons by rurality. Methods We conducted a retrospective cohort study of US adults sampled between January 1 and December 20, 2021, from the National COVID Cohort Collaborative (N3C). Using Kaplan-Meier and Cox-Proportional Hazards models adjusted for demographic differences and comorbid conditions, we assessed impact of rurality, county vaccine hesitancy, and county vaccination rates on risk of BTI over 180 days following two mRNA COVID-19 vaccinations between January 1 and September 21, 2021. Additionally, Cox Proportional Hazards models assessed the risk of infection among adults without documented vaccinations. We secondarily assessed the odds of hospitalization and adverse COVID-19 events based on vaccination status using multivariable logistic regression during the study period. Results Our study population included 566,128 vaccinated and 1,724,546 adults without documented vaccination. Among vaccinated persons, rurality was associated with an increased risk of BTI (adjusted hazard ratio [aHR] 1.53, 95% confidence interval [CI] 1.42–1.64, for urban-adjacent rural and 1.65, 1.42–1.91, for nonurban-adjacent rural) compared to urban dwellers. Compared to low vaccine-hesitant counties, higher risks of BTI were associated with medium (1.07, 1.02–1.12) and high (1.33, 1.23–1.43) vaccine-hesitant counties. Compared to counties with high vaccination rates, a higher risk of BTI was associated with dwelling in counties with low vaccination rates (1.34, 1.27–1.43) but not medium vaccination rates (1.00, 0.95–1.07). Community factors were also associated with higher odds of SARS-CoV-2 infection among persons without a documented vaccination. Vaccinated persons with SARS-CoV-2 infection during the study period had significantly lower odds of hospitalization and adverse events across all geographic areas and community exposures. Conclusions Our findings suggest that community factors are associated with an increased risk of BTI, particularly in rural areas and counties with high vaccine hesitancy. Communities, such as those in rural and disproportionately vaccine hesitant areas, and certain groups at high risk for adverse breakthrough events, including immunosuppressed/compromised persons, should continue to receive public health focus, targeted interventions, and consistent guidance to help manage community spread as vaccination protection wanes.

Community risks for SARS-CoV-2 infection among fully vaccinated US adults by rurality: A retrospective cohort study from the National COVID Cohort Collaborative

Susan L. Santangelo

Papers

Conclusion: Implications for Psychiatry and Neuropsychology

Appraising Circuit-Centered Neurophenotypes

Introduction and Structure of the Volume

Community risks for SARS-CoV-2 infection among fully vaccinated US adults by rurality: A retrospective cohort study from the National COVID Cohort Collaborative

Explaining Relapse to Opiate Addiction Following Successful Completion of Treatment: (496822006-010)