First use of anatomical networks to study modularity and integration of heads, forelimbs and hindlimbs in abnormal anencephalic and cyclopic vs normal human development

Abstract

The ill-named “logic of monsters” hypothesis of Pere Alberch - one of the founders of modern evo-devo - emphasized the importance of “internal rules” due to strong developmental constraints, linked teratologies to developmental processes and patterns, and contradicted hypotheses arguing that birth defects are related to a chaotic and random disarray of developmental mechanisms. We test these hypotheses using, for the first time, anatomical network analysis (AnNA) to study and compare the musculoskeletal modularity and integration of both the heads and the fore- and hindlimbs of abnormal cyclopic trisomy 18 and anencephalic human fetuses, and of normal fetal, newborn, and adult humans. Our previous works have shown that superficial gross anatomical analyses of these specimens strongly support the “logic of monsters” hypothesis, in the sense that there is an ‘order’ or ‘logic’ within the gross anatomical patterns observed in both the normal and abnormal individuals. Interestingly, the results of the AnNA done in the present work reveal a somewhat different pattern: at least concerning the musculoskeletal modules obtained in our AnNA, we observe a hybrid between the “logic of monsters” and the “lack of homeostasis” hypotheses. For instance, as predicted by the latter hypothesis, we found a high level of left-right asymmetry in the forelimbs and/or hindlimbs of the abnormal cyclopic trisomy 18 and anencephalic human fetuses. That is, a network analysis of the organization of/connection between the musculoskeletal structures of these fetuses reveals a more “chaotic” pattern than that detected by superficial gross anatomical comparisons. We discuss the broader developmental, evolutionary, and medical implications of these results.

Birds have peramorphic skulls, too: anatomical network analyses reveal oppositional heterochronies in avian skull evolution

“…Beside the ontogenetic signal in network parameters, many taxa in our sample, including non-avian theropods, show a leftright asymmetry in modularity, which is caused when paired bones are assigned to different modules or unpaired bones do not form their own module, but are assigned either to a left or right module. Similar asymmetries were previously found in skull network analyses of amniote and synapsid skulls 11,31 and the skull muscularity of primates and deformed humans 32,33 . On the Fig.…”

“…However, Powell et al 32 described an increase of module asymmetry within the head and neck muscles of simiiform primates, which they interpreted to be related to more complex, asymmetrical facial expressions. Diogo et al 33 further found that developmental deformation during embryogenesis increase module asymmetry. These two examples indicate that left-right asymmetry may not entirely be a methodological artefact, but could have a true biological meaning.…”

Phylogeny and foraging behaviour shape modular morphological variation in bat humeri

“…Within-bone modularity has been reported in felid vertebrae, suggesting a developmental signal reflecting ontogenetic similarities (Randau & Goswami, 2017). Postcranial modularity in mammals has been studied between groups of bones representing functional units, such as the vertebral column in felids , and the appendicular skeleton (Conaway et al, 2018;Diogo et al, 2019;Goswami et al, 2014;Martín-Serra et al, 2014).…”

A node-based informed modularity strategy to identify organizational modules in anatomical networks

“…The vertebrate skull has attracted most of the research on morphological modularity ( Esteve-Altava, 2017b ). Here, anatomical network studies have tried to unveil the topological units of organization to understand how they vary in evolution ( Arnold et al, 2017 ; Esteve-Altava et al, 2015 ; Plateau and Foth, 2020 ; Werneburg et al, 2019 ), but also in normal and pathological development ( Diogo et al, 2019 ; Esteve-Altava and Rasskin-Gutman, 2015 ). Moreover, some other studies have applied network methods to identify modules of landmark-based morphometric correlations rather than topological relations ( Ivan Perez et al, 2009 ; Suzuki, 2013 ).…”