Publications search

Pillai & Meng (Pillai & Meng 2016 Ann. Stat.44, 2089-2097; p. 2091) speculated that 'the dependence among [random variables, rvs] can be overwhelmed by the heaviness of their marginal tails ..'. We give examples of statistical models that support this speculation. While under natural conditions the sample correlation of regularly varying (RV) rvs converges to a generally random limit, this limit is zero when the rvs are the reciprocals of powers greater than one of arbitrarily (but imperfectly) positively or negatively correlated normals. Surprisingly, the sample correlation of these RV rvs multiplied by the sample size has a limiting distribution on the negative half-line. We show that the asymptotic scaling of Taylor's Law (a power-law variance function) for RV rvs is, up to a constant, the same for independent and identically distributed observations as for reciprocals of powers greater than one of arbitrarily (but imperfectly) positively correlated normals, whether those powers are the same or different. The correlations and heterogeneity do not affect the asymptotic scaling. We analyse the sample kurtosis of heavy-tailed data similarly. We show that the least-squares estimator of the slope in a linear model with heavy-tailed predictor and noise unexpectedly converges much faster than when they have finite variances.

The development of neutralizing antibodies (NAbs) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) following infection or vaccination is likely to be critical for the development of sufficient population immunity to drive cessation of the coronavirus disease of 2019 (COVID-19) pandemic. A large number of serologic tests, platforms, and methodologies are being employed to determine seroprevalence in populations to select convalescent plasma samples for therapeutic trials and to guide policies about reopening. However, the tests have substantial variations in sensitivity and specificity, and their ability to quantitatively predict levels of NAbs is unknown. We collected 370 unique donors enrolled in the New York Blood Center Convalescent Plasma Program between April and May of 2020. We measured levels of antibodies in convalescent plasma samples using commercially available SARS-CoV-2 detection tests and in-house enzyme-linked immunosorbent assays (ELISAs) and correlated serological measurements with NAb activity measured using pseudotyped virus particles, which offer the most informative assessment of antiviral activity of patient sera against viral infection. Our data show that a large proportion of convalescent plasma samples have modest antibody levels and that commercially available tests have various degrees of accuracy in predicting NAb activity. We found that the Ortho anti-SARS-CoV-2 total Ig and IgG high-throughput serological assays (HTSAs) and the Abbott SARS-CoV-2 IgG assay quantify levels of antibodies that strongly correlate with the results of NAb assays and are consistent with gold standard ELISA results. These findings provide immediate clinical relevance to serology results that can be equated to NAb activity and could serve as a valuable roadmap to guide the choice and interpretation of serological tests for SARSCoV-2.

The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment(1). The origins of specific compounds are known, including metabolites that are highly heritable(2,3), or those that are influenced by the gut microbiome(4), by lifestyle choices such as smoking(5), or by diet(6). However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites-in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts(7,8) that were not available to us when we trained the algorithms. We used feature attribution analysis(9) to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites. The levels of 1,251 metabolites are measured in 475 phenotyped individuals, and machine-learning algorithms reveal that diet and the microbiome are the determinants with the strongest predictive power for the levels of these metabolites.

Antibodies against viral pathogens represent promising therapeutic agents for the control of infection, and their antiviral efficacy has been shown torequire the coordinated function of both the Fab and Fc domains(1). The Fc domain engages a wide spectrum of receptors on discrete cells of the immune system to trigger the clearance of viruses and subsequent killing of infected cells(1-4). Here we report that Fc engineering of anti-influenza IgG monoclonal antibodies for selective binding to the activating Fc. receptor Fc.RIIa results in enhanced ability to prevent or treat lethal viral respiratory infection in mice, with increased maturation of dendritic cells and the induction of protective CD8(+) T cell responses. These findings highlight the capacity for IgG antibodies to induce protective adaptive immunity to viral infection when they selectively activate a dendritic cell and T cell pathway, with important implications for the development of therapeutic antibodies with improved antiviral efficacy against viral respiratory pathogens.

The discovery of T-cell responses to SARS-CoV-2 in non-infected individuals indicates cross-reactive immune memory from prior exposure to human coronaviruses (HCoV) that cause the common cold. This raises the possibility that "immunity" could exist within populations at rates that may be higher than serology studies estimate. Besides specialized research labs, however, there is limited ability to measure HCoV CD4+ and CD8+ T-cell responses to SARS-CoV-2 infection, which currently impedes interpretation of any potential correlation between COVID-19 disease pathogenesis and the calibration of pandemic control measures. Given this limited testing ability, an alternative approach would be to exploit the large cohort of currently available data from which statistically significant associations may be generated. This would necessitate the merging of several public databases including patient and contact tracing, which could be created by relevant public health organizations. Including data from both symptomatic and asymptomatic patients in SARS-CoV-2 databases and surveillance systems could provide the necessary information to allow for more informed decisions.

Susceptibility to herpes simplex virus type 1 (HSV-1) encephalitis (HSE-1) in otherwise healthy individuals, in the course of primary infection, can be caused by single-gene inborn errors of Toll-like receptor 3 (TLR3) dependent, interferon (IFN)-alpha/beta-mediated immunity,(1,2) or by single-gene inborn errors of snoRNA31.(3) These variations underlie infections of the forebrain, whereas mutations of DBR1 underlie infections of the brainstem.(3) HSV-2 encephalitis (HSE-2) is typically observed in neonates, albeit also rarely in older children and adults.(4) Its manifestations include altered level of consciousness, cranial neuropathies or more extensive brainstem encephalitis, hemiparesis, hemisensory loss, and permanent neurologic deficit.(4) MRI in HSE-2 may show normal findings, nonspecific white matter, orbitofrontal, mesial temporal lobe, or brainstem lesions. Inborn errors of immunity underlying HSE-2 have not been described.

Efficient and faithful replication of the genome is essential to maintain genome stability. Replication is carried out by a multi protein complex called the replisome, which encounters numerous obstacles to its progression. Failure to bypass these obstacles results in genome instability and may facilitate errors leading to disease. Cells use accessory helicases that help the replisome bypass difficult barriers. All eukaryotes contain the accessory helicase Pif1, which tracks in a 5 '-3 ' direction on single-stranded DNA and plays a role in genome maintenance processes. Here, we reveal a previously unknown role for Pif1 in replication barrier bypass. We use an in vitro reconstituted Saccharomyces cerevisiae replisome to demonstrate that Pif1 enables the replisome to bypass an inactive (i.e., dead) Cas9 (dCas9) R-loop barrier. Interestingly, dCas9 R-loops targeted to either strand are bypassed with similar efficiency. Furthermore, we employed a single molecule fluorescence visualization technique to show that Pif1 facilitates this bypass by enabling the simultaneous removal of the dCas9 protein and the R-loop. We propose that Pif1 is a general displacement helicase for replication bypass of both R-loops and protein blocks.

Primate brains have evolved to understand and engage with their social world. Much about the structure of this world can be gleaned from social interactions. Circuits for the analysis of and participation in social interactions have now been mapped. Increased knowledge about their functional specializations and relative spatial locations promises to greatly improve the understanding of the functional organization of the primate social brain. Detailed electrophysiology, as in the case of the face-processing network, of local operations and functional interactions between areas is necessary to uncover neural mechanisms and computation principles of social cognition. New naturalistic behavioral paradigms, behavioral tracking, and new analytical approaches for parallel non-stationary data will be important components toward a neuroscientific theory of primates' interactive minds.

Telomere shortening is a presumed tumor suppressor pathway that imposes a proliferative barrier (the Hayflick limit) during tumorigenesis. This model predicts that excessively long somatic telomeres predispose to cancer. Here, we describe cancer-prone families with two unique TINF2 mutations that truncate TIN2, a shelterin subunit that controls telomere length. Patient lymphocyte telomeres were unusually long. We show that the truncated TIN2 proteins do not localize to telomeres, suggesting that the mutations create loss-of-function alleles. Heterozygous knock-in of the mutations or deletion of one copy of TINF2 resulted in excessive telomere elongation in clonal lines, indicating that TINF2 is haploinsufficient for telomere length control. In contrast, telomere protection and genome stability were maintained in all heterozygous clones. The data establish that the TINF2 truncations predispose to a tumor syndrome. We conclude that TINF2 acts as a haploinsufficient tumor suppressor that limits telomere length to ensure a timely Hayflick limit.