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Review
. 2021 May;17(5):1065-1076.
doi: 10.1080/15548627.2020.1752511. Epub 2020 Apr 17.

Sex differences in autophagy-mediated diseases: toward precision medicine

Affiliations
Review

Sex differences in autophagy-mediated diseases: toward precision medicine

Dangtong Shang et al. Autophagy. 2021 May.

Abstract

Nearly all diseases in humans, to a certain extent, exhibit sex differences, including differences in the onset, progression, prevention, therapy, and prognosis of diseases. Accumulating evidence shows that macroautophagy/autophagy, as a mechanism for development, differentiation, survival, and homeostasis, is involved in numerous aspects of sex differences in diseases such as cancer, neurodegeneration, and cardiovascular diseases. Advances in our knowledge regarding sex differences in autophagy-mediated diseases have enabled an understanding of their roles in human diseases, although the underlying molecular mechanisms of sex differences in autophagy remain largely unexplored. In this review, we discuss current advances in our insight into the biology of sex differences in autophagy and disease, information that will facilitate precision medicine.Abbreviations: AD: Azheimer disease; AMBRA1: autophagy and beclin 1 regulator 1; APP: amyloid beta precursor protein; AR: androgen receptor; AMPK: AMP-activated protein kinase; ATG: autophagy related; ATP6AP2: ATPase H+ transporting accessory protein 2; BCL2L1: BCL2 like 1; BECN1: beclin 1; CTSD: cathepsin D; CYP19A1: cytochrome P450 family 19 subfamily A member 1; DSD: disorders of sex development; eALDI: enhancer alternate long-distance initiator; ESR1: estrogen receptor 1; ESR2: estrogen receptor 2; FYCO1: FYVE and coiled-coil domain autophagy adaptor 1; GABARAP: GABA type A receptor-associated protein; GLA: galactosidase alpha; GTEx: genotype-tissue expression; HDAC6: histone deacetylase 6; I-R: ischemia-reperfusion; LAMP2: lysosomal associated membrane protein 2; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; MTOR: mechanistic target of rapamycin kinase; m6A: N6-methyladenosine; MYBL2: MYB proto-oncogene like 2; PIK3C3: phosphatidylinositol 3-kinase catalytic subunit type 3; PSEN1: presenilin 1; PSEN2: presenilin 2; RAB9A, RAB9A: member RAS oncogene family; RAB9B, RAB9B: member RAS oncogene family; RAB40AL: RAB40A like; SF1: splicing factor 1; SOX9: SRY-box transcription factor 9; SRY: sex determining region Y; TFEB: transcription factor EB; ULK1: unc-51 like autophagy activating kinase 1; UVRAG: UV radiation resistance associated; VDAC2: voltage dependent anion channel 2; WDR45: WD repeat domain 45; XPDS: X-linked parkinsonism and spasticity; YTHDF2: YTH N6-methyladenosine RNA binding protein 2.

Keywords: Autophagy; disease; health; precision medicine; sex.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1.
Figure 1.
Major types of human diseases with sex differences. (A) Graphical depiction shows typical diseases with sex differences in various systems. Representative organs/tissues, such as brain, heart, lung, liver, gut, kidney, blood, bone, adipose, testis, and ovary, are associated with relevant diseases in men and women, such as obesity, cardiovascular diseases, and Alzheimer disease. (B) Schematic diagram of the most common cancers estimated in men and women in the United States in 2019. Case number and death percentage by sex are shown. Data are from the American Cancer Society 2019 [12]
Figure 2.
Figure 2.
Sex determination and differentiation in human. (A) Schematic depiction of the evolution of sex chromosomes X and Y in humans, highlighting the differentiation of the X and Y chromosomes. XX determines female, whereas XY determines male. The X and Y chromosomes originated from an ordinary pair of autosomes (G/G) ~350 million years ago (MYA). During the evolutionary process, the X chromosome remains relatively stable, but the Y chromosome is dynamic and degenerate. The Y chromosome is progressively degraded after acquiring a male-determining role. Sex-determining gene SRY on the Y chromosome evolved from SOX3 on chromosome X. (B) SRY starts male differentiation. If there is no SRY, the embryos will default toward female development. SRY, as a transcription factor, induces testis differentiation, and subsequent male development through supporting cells to produce sex hormones, such as androgens (testosterone) and estrogens (estradiol). These hormones act via binding their receptors, including AR, ESR1, and ESR2, in the nucleus. Then, they will activate transcription of their target genes to induce sex differentiation. (C) AR is expressed broadly in many tissues, not only in reproductive organs. RNA-Seq data were downloaded from BioProject: PRJEB4337
Figure 3.
Figure 3.
Schematic diagram of the autophagy pathway from phagophore induction, expansion, and maturation, highlighting the transcriptional regulation of autophagy genes by sex hormone receptors AR and ESR1. The regulatory relationship of autophagy genes by AR and ESR1 are indicated by dotted arrows, AR in red and ESR1 in purple
Figure 4.
Figure 4.
Transcriptional regulation of autophagy genes by sex hormone receptors AR and ESR1 in humans, experimentally confirmed. Autophagy genes for phagophore induction, expansion, lysosome fusion, and lysosome genesis are shown in groups with different colors. The binding sites of the sex hormone receptors AR and ESR1 on autophagy genes are indicated in purple (AR) or blue (ESR1) ovals. The sequence logos of AR and ESR1 for binding sites are shown in the lower panel. The regulatory relationships of autophagy genes by AR and ESR1 were retrieved from references mentioned in the text, and related position information of AR and ESR1 binding was obtained by mapping to the human genome hg38 (http://genome-asia.ucsc.edu/)
Figure 5.
Figure 5.
Transcriptional regulation of autophagy genes by sex hormone receptors ESR1 and ESR2 in humans, analyzed with bioinformatics. Autophagy genes for phagophore induction, expansion, and fusion with lysosomes are shown in different colors. The regulations of relationships were predicted through bioinformatics analysis by Türei et al (2015) [76]

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