Estimating Peer Effects in Longitudinal Dyadic Data Using Instrumental Variables

The identification of causal peer effects (also known as social contagion or induction) from observational data in social networks is challenged by two distinct sources of bias: latent homophily and unobserved confounding. In this paper, we investigate how causal peer effects of traits and behaviors can be identified using genes (or other structurally isomorphic variables) as instrumental variables (IV) in a large set of data generating models with homophily and confounding. We use directed acyclic graphs to represent these models and employ multiple IV strategies and report three main identification results. First, using a single fixed gene (or allele) as an IV will generally fail to identify peer effects if the gene affects past values of the treatment. Second, multiple fixed genes/alleles, or, more promisingly, time-varying gene expression, can identify peer effects if we instrument exclusion violations as well as the focal treatment. Third, we show that IV identification of peer effects remains possible even under multiple complications often regarded as lethal for IV identification of intra-individual effects, such as pleiotropy on observables and unobservables, homophily on past phenotype, past and ongoing homophily on genotype, inter-phenotype peer effects, population stratification, gene expression that is endogenous to past phenotype and past gene expression, and others. We apply our identification results to estimating peer effects of body mass index (BMI) among friends and spouses in the Framingham Heart Study. Results suggest a positive causal peer effect of BMI between friends

State-level income inequality and mortality among infants born in the United States 2007-2010: A Cohort Study

BACKGROUND: United States state-level income inequality is positively associated with infant mortality in ecological studies. We exploit spatiotemporal variations in a large dataset containing individual-level data to conduct a cohort study and to investigate whether current income inequality and increases in income inequality are associated with infant and neonatal mortality risk over the period of the 2007-2010 Great Recession in the United States. METHODS: We used data on 16,145,716 infants and their mothers from the 2007-2010 United States Statistics Linked Infant Birth and Death Records. Multilevel logistic regression was used to determine whether 1) US state-level income inequality, as measured by Z-transformed Gini coefficients in the year of birth and 2) change in Gini coefficient between 1990 and year of birth (2007-2010), predicted infant or neonatal mortality. Our analyses adjusted for both individual and state-level covariates. RESULTS: From 2007 to 2010 there were 98,002 infant deaths: an infant mortality rate of 6.07 infant deaths per 1000 live births. When controlling for state and individual level characteristics, there was no significant relationship between Gini Z-score and infant mortality risk. However, the observed increase in the Gini Z-score was associated with a small but significant increase likelihood of infant mortality (AOR = 1.03 to 1.06 from 2007 to 2010). Similar findings were observed when the neonatal mortality was the outcome (AOR = 1.05 to 1.13 from 2007 to 2010). CONCLUSIONS: Infants born in states with greater changes in income inequality between 1990 and 2007 to 2010 experienced a greater likelihood of infant and neonatal mortality

Cohort of Birth Modifies the Association between FTO Genotype and BMI

A substantial body of research has explored the relative roles of genetic and environmental factors on phenotype expression in humans. Recent research has also sought to identify gene-environment (or g-by-e) interactions, with mixed success. One potential reason for these mixed results may relate to the fact that genetic effects might be modified by changes in the environment over time. For example, the noted rise of obesity in the United States in the latter part of the 20th century might reflect an interaction between genetic variation and changing environmental conditions that together affect the penetrance of genetic influences. To evaluate this hypothesis, we use longitudinal data from the Framingham Heart Study collected over 30 y from a geographically relatively localized sample to test whether the well-documented association between the rs993609 variant of the FTO (fat mass and obesity associated) gene and body mass index (BMI) varies across birth cohorts, time period, and the lifecycle. Such cohort and period effects integrate many potential environmental factors, and this gene-by-environment analysis examines interactions with both time-varying contemporaneous and historical environmental influences. Using constrained linear age-period-cohort models that include family controls, we find that there is a robust relationship between birth cohort and the genotype-phenotype correlation between the FTO risk allele and BMI, with an observed inflection point for those born after 1942. These results suggest genetic influences on complex traits like obesity can vary over time, presumably because of global environmental changes that modify allelic penetrance

Auditory cues and inhibition of return: the importance of oculomotor activation

We studied the effects of eccentric auditory cues to clarify the conditions that evoke inhibition of return (IOR). We found that auditory cues positioned 12° to the left or right of midline failed to produce IOR whereas visual cues produced IOR under the same experimental conditions. The eccentric auditory cues elicited automatic orienting as evidenced by more rapid detection of cued than uncued visual targets at short stimulus onset asynchrony. Yet these same cues did not produce IOR unless observers were required to saccade to the cue and back to center before generating a manual detection response. Thus, under the conditions examined herein automatic orienting was not sufficient to evoke IOR, but oculomotor activation appeared to be essential. The functional significance of IOR and the question of modality-specific orienting processes are considered.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46532/1/221_2004_Article_BF00227185.pd

Exome sequencing followed by large-scale genotyping suggests a limited role for moderately rare risk factors of strong effect in schizophrenia.

Schizophrenia is a severe psychiatric disorder with strong heritability and marked heterogeneity in symptoms, course, and treatment response. There is strong interest in identifying genetic risk factors that can help to elucidate the pathophysiology and that might result in the development of improved treatments. Linkage and genome-wide association studies (GWASs) suggest that the genetic basis of schizophrenia is heterogeneous. However, it remains unclear whether the underlying genetic variants are mostly moderately rare and can be identified by the genotyping of variants observed in sequenced cases in large follow-up cohorts or whether they will typically be much rarer and therefore more effectively identified by gene-based methods that seek to combine candidate variants. Here, we consider 166 persons who have schizophrenia or schizoaffective disorder and who have had either their genomes or their exomes sequenced to high coverage. From these data, we selected 5,155 variants that were further evaluated in an independent cohort of 2,617 cases and 1,800 controls. No single variant showed a study-wide significant association in the initial or follow-up cohorts. However, we identified a number of case-specific variants, some of which might be real risk factors for schizophrenia, and these can be readily interrogated in other data sets. Our results indicate that schizophrenia risk is unlikely to be predominantly influenced by variants just outside the range detectable by GWASs. Rather, multiple rarer genetic variants must contribute substantially to the predisposition to schizophrenia, suggesting that both very large sample sizes and gene-based association tests will be required for securely identifying genetic risk factors. © 2012 The American Society of Human Genetics

Clinical impact of recurrently mutated genes on lymphoma diagnostics

Similar to the inherent clinical heterogeneity of most, if not all, lymphoma entities, the genetic landscape of these tumors is markedly complex in the majority of cases, with a rapidly growing list of recurrently mutated genes discovered in recent years by next-generation sequencing technology. Whilst a few genes have been implied to have diagnostic, prognostic and even predictive impact, most gene mutations still require rigorous validation in larger, preferably prospective patient series, to scrutinize their potential role in lymphoma diagnostics and patient management. In selected entities, a predominantly mutated gene is identified in almost all cases (e.g. Waldenström's macroglobulinemia/lymphoplasmacytic lymphoma and hairy-cell leukemia), while for the vast majority of lymphomas a quite diverse mutation pattern is observed, with a limited number of frequently mutated genes followed by a seemingly endless tail of genes with mutations at a low frequency. Herein, the European Expert Group on NGS-based Diagnostics in Lymphomas (EGNL) summarizes the current status of this ever-evolving field, and, based on the present evidence level, segregates mutations into the following categories: i) immediate impact on treatment decisions, ii) diagnostic impact, iii) prognostic impact, iv) potential clinical impact in the near future, or v) should only be considered for research purposes. In the coming years, coordinated efforts aiming to apply targeted next-generation sequencing in large patient series will be needed in order to elucidate if a particular gene mutation will have an immediate impact on the lymphoma classification, and ultimately aid clinical decision making

Gene conversion in human rearranged immunoglobulin genes

Over the past 20 years, many DNA sequences have been published suggesting that all or part of the V<sub>H</sub> segment of a rearranged immunoglobulin gene may be replaced in vivo. Two different mechanisms appear to be operating. One of these is very similar to primary V(D)J recombination, involving the RAG proteins acting upon recombination signal sequences, and this has recently been proven to occur. Other sequences, many of which show partial V<sub>H</sub> replacements with no addition of untemplated nucleotides at the V<sub>H</sub>–V<sub>H</sub> joint, have been proposed to occur by an unusual RAG-mediated recombination with the formation of hybrid (coding-to-signal) joints. These appear to occur in cells already undergoing somatic hypermutation in which, some authors are convinced, RAG genes are silenced. We recently proposed that the latter type of V<sub>H</sub> replacement might occur by homologous recombination initiated by the activity of AID (activation-induced cytidine deaminase), which is essential for somatic hypermutation and gene conversion. The latter has been observed in other species, but not in human Ig genes, so far. In this paper, we present a new analysis of sequences published as examples of the second type of rearrangement. This not only shows that AID recognition motifs occur in recombination regions but also that some sequences show replacement of central sections by a sequence from another gene, similar to gene conversion in the immunoglobulin genes of other species. These observations support the proposal that this type of rearrangement is likely to be AID-mediated rather than RAG-mediated and is consistent with gene conversion

Impact of age on NIS2+™ and other non-invasive blood tests for the evaluation of liver disease and detection of at-risk MASH

\ua9 2024 The Author(s)Background & Aims: Robust performance of non-invasive tests (NITs) across ages is critical to assess liver disease among patients with metabolic dysfunction-associated liver disease (MASLD). We evaluated the impact of age on the performance of NIS2+™ vs. other NITs. Methods: An analysis cohort (N = 1,926) with biopsy-proven MASLD was selected among individuals screened for the phase III RESOLVE-IT clinical trial and divided into ≤45, 46–55, 56–64, and ≥65 years groups. To avoid potential confounding effects, a well-balanced cohort (n = 708; n = 177/age group) was obtained by applying a propensity score-matching algorithm to the analysis cohort. Baseline values of biomarkers and NITs were compared across age groups using one-way ANOVA, and the impact of age and histology were compared through three-way ANOVA. The impact of age on NIT performance for the detection of at-risk metabolic dysfunction-associated steatohepatitis (MASH; MASLD activity score [MAS] ≥4 and fibrosis stage [F] ≥2) was also evaluated. Results: Age did not affect the distributions of NIS2+™ and APRI (aspartate aminotransferase-to-platelet ratio index), but significantly (p <0.0001) impacted those of NFS (NAFLD fibrosis score), FIB-4 (Fibrosis-4 index), and Enhanced Liver Fibrosis (ELF™) score. NIS2+™ was the only NIT on which fibrosis and MAS exerted a moderate to large effect. While the impact of fibrosis on APRI was moderate, that of MAS was low. The impact of age on FIB-4 and NFS was larger than that of fibrosis. NIS2+™ exhibited the highest AUROC values for detecting at-risk MASH across age groups, with stable performances irrespective of cut-offs. Conclusions: NIS2+™ was not significantly impacted by age and was sensitive to both fibrosis and MAS grade, demonstrating a robust performance to rule in/out at-risk MASH with fixed cut-offs. Impact and Implications: While metabolic dysfunction-associated steatotic liver disease (MASLD) can affect individuals of all ages, patient age could represent an important confounding factor when interpreting non-invasive test (NIT) results, highlighting the need for reliable and efficient NITs that are not impacted by age and that could be interpreted with fixed cut-offs, irrespective of patient age. We report the impact of age on different well-established NITs – among those tested, only two panels, NIS2+™ and APRI, were not impacted by age and can be used and interpreted independently of patient age. NIS2+™ was also sensitive to both fibrosis and MAS, further confirming its efficiency for the detection of the composite endpoint of at-risk MASH and its potential as a valuable candidate for large-scale implementation in clinical practice and clinical trials