Polygenic scores for major depressive disorder and depressive symptoms predict response to lithium in patients with bipolar disorder, bioRxiv, 2018-10-22

AbstractBackgroundLithium is a first-line medication for bipolar disorder (BD), but only ~30% of patients respond optimally to the drug. Since genetic factors are known to mediate lithium treatment response, we hypothesized whether polygenic susceptibility to the spectrum of depression traits is associated with treatment outcomes in patients with BD. In addition, we explored the potential molecular underpinnings of this relationship.MethodsWeighted polygenic scores (PGSs) were computed for major depressive disorder (MDD) and depressive symptoms (DS) in BD patients from the Consortium on Lithium Genetics (ConLi+Gen; n=2,586) who received lithium treatment. Lithium treatment outcome was assessed using the ALDA scale. Summary statistics from genome-wide association studies (GWAS) in MDD (130,664 cases and 330,470 controls) and DS (n=161,460) were used for PGS weighting. Associations between PGSs of depression traits and lithium treatment response were assessed by binary logistic regression. We also performed a cross-trait meta-GWAS, followed by Ingenuity® Pathway Analysis.OutcomesBD patients with a low polygenic load for depressive traits were more likely to respond well to lithium, compared to patients with high polygenic load (MDD OR =1.64 [95%CI 1.26-2.15], lowest vs highest PGS quartiles; DS OR=1.53 [95%CI 1.18-2.00]). Associations were significant for type 1, but not type 2 BD. Cross-trait GWAS and functional characterization implicated voltage-gated potassium channels, insulin-related pathways, mitogen-activated protein-kinase (MAPK) signaling, and miRNA expression.InterpretationGenetic loading to depression traits in BD patients lower their odds of responding optimally to lithium. Our findings support the emerging concept of a lithium-responsive biotype in BD.FundingSee attached details

Predicting the Future with Multi-scale Successor Representations, bioRxiv, 2018-10-22

AbstractThe successor representation (SR) is a candidate principle for generalization in reinforcement learning, computational accounts of memory, and the structure of neural representations in the hippocampus. Given a sequence of states, the SR learns a predictive representation for every given state that encodes how often, on average, each upcoming state is expected to be visited, even if it is multiple steps ahead. A discount or scale parameter determines how many steps into the future SR’s generalizations reach, enabling rapid value computation, subgoal discovery, and flexible decision-making in large trees. However, SR with a single scale could discard information for predicting both the sequential order of and the distance between states, which are common problems in navigation for animals and artificial agents. Here we propose a solution an ensemble of SRs with multiple scales. We show that the derivative of multi-scale SR can reconstruct both the sequence of expected future states and estimate distance to goal. This derivative can be computed linearly we show that a multi-scale SR ensemble is the Laplace transform of future states, and the inverse of this Laplace transform is a biologically plausible linear estimation of the derivative. Multi-scale SR and its derivative could lead to a common principle for how the medial temporal lobe supports both map-based and vector-based navigation.

The population history of northeastern Siberia since the Pleistocene, bioRxiv, 2018-10-22

ABSTRACTFar northeastern Siberia has been occupied by humans for more than 40 thousand years. Yet, owing to a scarcity of early archaeological sites and human remains, its population history and relationship to ancient and modern populations across Eurasia and the Americas are poorly understood. Here, we analyze 34 ancient genome sequences, including two from fragmented milk teeth found at the ~31.6 thousand-year-old (kya) Yana RHS site, the earliest and northernmost Pleistocene human remains found. These genomes reveal complex patterns of past population admixture and replacement events throughout northeastern Siberia, with evidence for at least three large-scale human migrations into the region. The first inhabitants, a previously unknown population of “Ancient North Siberians” (ANS), represented by Yana RHS, diverged ~38 kya from Western Eurasians, soon after the latter split from East Asians. Between 20 and 11 kya, the ANS population was largely replaced by peoples with ancestry related to present-day East Asians, giving rise to ancestral Native Americans and “Ancient Paleosiberians” (AP), represented by a 9.8 kya skeleton from Kolyma River. AP are closely related to the Siberian ancestors of Native Americans, and ancestral to contemporary communities such as Koryaks and Itelmen. Paleoclimatic modelling shows evidence for a refuge during the last glacial maximum (LGM) in southeastern Beringia, suggesting Beringia as a possible location for the admixture forming both ancestral Native Americans and AP. Between 11 and 4 kya, AP were in turn largely replaced by another group of peoples with ancestry from East Asia, the “Neosiberians” from which many contemporary Siberians derive. We detect gene flow events in both directions across the Bering Strait during this time, influencing the genetic composition of Inuit, as well as Na Dene-speaking Northern Native Americans, whose Siberian-related ancestry components is closely related to AP. Our analyses reveal that the population history of northeastern Siberia was highly dynamic throughout the Late Pleistocene and Holocene. The pattern observed in northeastern Siberia, with earlier, once widespread populations being replaced by distinct peoples, seems to have taken place across northern Eurasia, as far west as Scandinavia.

Transduction of the Geomagnetic Field as Evidenced from Alpha-band Activity in the Human Brain, bioRxiv, 2018-10-20

AbstractMagnetoreception, the perception of the geomagnetic field, is a sensory modality well-established across all major groups of vertebrates and some invertebrates, but its presence in humans has been tested rarely, yielding inconclusive results. We report here a strong, specific human brain response to ecologically-relevant rotations of Earth-strength magnetic fields. Following geomagnetic stimulation, a drop in amplitude of EEG alpha oscillations (8-13 Hz) occurred in a repeatable manner. Termed alpha event-related desynchronization (alpha-ERD), such a response is associated with sensory and cognitive processing of external stimuli. Biophysical tests showed that the neural response was sensitive to the dynamic components and axial alignment of the field but also to the static components and polarity of the field. This pattern of results implicates ferromagnetism as the biophysical basis for the sensory transduction and provides a basis to start the behavioral exploration of human magnetoreception.

Bridging the divide bacteria synthesizing archaeal membrane lipids, bioRxiv, 2018-10-19

Archaea synthesize membranes of isoprenoid lipids that are ether-linked to glycerol, while BacteriaEukarya produce membranes consisting of ester-bound fatty acids. This dichotomy in membrane lipid composition or ‘lipid divide’ is believed to have arisen after the Last Universal Common Ancestor (LUCA). A leading hypothesis is that LUCA possessed a ‘mixed heterochiral archaealbacterial membrane’, however no natural microbial representatives supporting this scenario have been shown to exist today. Here, we demonstrate that bacteria of the Fibrobacteres-Chlorobi-Bacteroidetes (FCB) group superphylum and related candidate phyla encode a complete pathway for archaeal membrane lipid biosynthesis in addition to the bacterial fatty acid membrane pathway. Key genes were expressed in the environment and their recombinant expression in E. coli resulted in the formation of a ‘mixed archaealbacterial membrane’. Our results support the existence of ‘mixed membranes’ in natural environments and their stability over large evolutionary timescales, thereby bridging a once-thought fundamental divide in biology.

Explaining heritable variance in human character, bioRxiv, 2018-10-19